3rd Student Conference on Operational Research Nottingham, UK 20-22 April 2012 Programme and Abstracts Directions A very warm Welcome to SCOR 2012 We are delighted that you are joining us at the University of Nottingham for the 3rd Student Conference on Operational Research (SCOR 2012). We have delegates who have travelled from across Europe and from further afield and we are glad to see you have all arrived safely. SCOR 2012 is a conference aimed at students who are studying Operational Research, Management Science or a related field. In planning this conference, our objective has been to provide a friendly environment in which students can share their work, practice their presentation skills, receive constructive feedback, and meet others who are researching similar topics. In addition to the high calibre of student speakers, we are very pleased to have five excellent invited speakers: Gavin Blackett (The OR Society), David Buxton (DSE Consulting Ltd.), Tony OвЂ™Connor (GORS), Vincent Knight (Cardiff University) and Louise Orpin (The OR Society). We have a full conference programme over the next three days, so please take a few minutes to read through the important information provided in this pack. The conference is fully catered, with the conference dinner being held on Friday evening. Please ensure that you read the information on page 6 regarding the location and provision of other meals. We hope you have a great time at the conference here in Nottingham. If we can do anything to help you over the weekend then please let us know. Thank you for joining us at SCOR 2012. The SCOR Committee 2012 Directions The conference will take place at the University Jubilee Campus. This is NOT the main campus of the university, but a little closer to the city centre of Nottingham. The University of Nottingham Jubilee Campus Wollaton Road Nottingham NG8 1BB, UK Phone: (+44) 115 846 6543 Fax: (+44) 115 846 7877 Contact numbers during the conference: Stefan Ravizza: (+44) 796 490 8133 Penny Holborn: (+44) 782 572 9540 Urszula Neuman: (+44) 784 561 4083 Detailed maps and directions can be found at: http://www.nottingham.ac.uk/about/visitorinformation/mapsanddirections/jubileecampus.aspx Travelling from East Midlands Airport: From East Midlands Airport you can take the Nottingham City TransportвЂ™s Skylink service. Buses leave from outside the Airport Arrivals hall. The journey takes 60 minutes and buses are every 30 minutes until 11.30pm, then hourly until 5am when the half hourly service resumes. You can also walk to the taxi rank on the terminal forecourt and take a direct taxi to the university. The cost of a single/one way journey is approximately ВЈ20. Taxis are normally available 24 hours. Travelling by Train: From London: St. Pancras. Tickets between London and Nottingham are available from the national rail website. There are also regular services to Nottingham from Birmingham, Derby, Leicester, Crewe, Sheffield, and Leeds (http://www.nationalrail.co.uk/). Turn right out of the main station exit (not the smaller, Station Street exit) for an easy 5 minute walk to the city centre. The Broadmarsh bus station is on the right, after approx 250m (Carrington Street). From M1 Motorway: Leave the M1 motorway at Junction 25 to join the A52 to Nottingham. After five miles turn left onto the A6514, Middleton Boulevard. Turn right at the next roundabout onto the A609 Wollaton Road. The main entrance to Jubilee Campus is clearly signposted on the right. SCOR 2012 3 Conference Registration and Accommodation Travelling from Nottingham: There are a number of bus services running from Nottingham to Jubilee Campus (вЂњthe Two", 28 and 30). More information can be found on the Trent Barton Website: http://www.trentbuses.co.uk/university/index.html. There are taxi ranks throughout the city and immediately adjacent to the main railway and bus stations. The journey to the campus takes approximately 15 minutes. Travelling by Taxi to Jubilee Campus: There are taxi ranks throughout the City Centre and immediately adjacent to the main railway and bus stations. The journey to the campus takes about 15 minutes. Taxi Companies: DG Cars Trent Cars Nottingham Cars Fast-Lane Cabs (+44) 115 960 7607 (+44) 115 950 5050 (+44) 115 970 0700 (+44) 115 950 1501 Parking on the Campus Parking in the car park in front of the halls of residence is available for SCOR students for the duration of the event (nonNottingham students only). When you arrive at the campus please indicate to the security gate that you are here for the SCOR conference and they will provide you with a security pass for your car as well as directions to the halls. Please note that the accommodation will not be available on the Friday until after 3pm therefore please proceed to the lecture theatre (for more information see the accommodation section). Conference Registration and Accommodation Delegates are asked to go straight to вЂњThe Exchange" (see map on page 8, building no 2) for the welcome buffet and registration, as access to the halls is only available from 3pm onwards. We have arranged for the bags to be left in a secure room during the first talks on Friday afternoon. Another room will be used to leave bags on the Sunday during the programme as guests are asked to check out of the halls before 10am. The conference will be opened by the Conference Chair, Stefan Ravizza, in вЂњThe Exchange" room LT2 at 1.15pm. The first session of the conference will begin at 2.45pm. For the full conference programme, see page 17. Southwell Hall (En-suite) The hall is a 2 minute walk across the campus from вЂњThe Exchange" where the initial welcome buffet and registration will be held. Access can be granted to bedrooms from 3pm onwards. The hall manager or assistant hall manager will check in guests and give you a room key from the hall reception. Keys are to be handed in to the main reception upon departure and any missing keys will be charged for. Guests are asked to retain their keys at all times. Internet Access These instructions clarify the procedures for visitors accessing the wireless network when the helpline is closed. It also highlights alternative methods to access the internet while at the University of Nottingham, when not a member of the university. A visitor is classed as anyone who is not a member of staff or a student of the University of Nottingham, including conference guests, ad-hoc visitors, etc. There are three ways to access the internet: вЂў Wired access in the halls of residence (SNS) вЂў Public access terminals in the halls of residence and walk-in PCвЂ™s in the libraries вЂў Wireless access in the public areas (UoN-Guest) The following information is for visitors to the university. Nottingham students should continue to use the information on the IS website at: http://www.nottingham.ac.uk/is/ 4 SCOR 2012 Conference Registration and Accommodation Wired Access in Halls of Residence (SNS) Each bedroom has access to the SNS network requiring a data cable which plugs into the data socket. In order to connect, a visitor should plug a data cable into their laptop and connect it to the data point. On opening your internet browser, you will be presented with the вЂњWelcome to the Student Network Service" screen. Visitors should click Visitor to continue, before being asked to confirm you agree to abide by the terms and conditions. The next stage will be to register your computer. All users will need to provide some details so that the university can contact them if necessary (for example in an emergency or abuse of the service). By clicking Continue, visitors are assumed to have agreed to these terms and conditions. After completing this final stage, you will be registered and can use the SNS for up to seven days. Public Access Terminals in the Halls of Residence and Walk-in PCвЂ™s in the Libraries Each university hall has been supplied with two PCs which connect to the university network, using a pre-supplied username and password (if these have been lost, the Staff helpline will be able to supply them). These PCs are configured exactly the same as the computer room PCs on campus. Wireless Access in the Public Areas (UoN-Guest) In public areas such as coffee bars or Junior Common Rooms, there is a wireless access point. Guests and visitors can use this to connect to the internet through the UoN-guest network. When in study bedrooms, the fixed line SNS point should be used (see section above). To access the guest wireless service, visitors simply need to select UoN-guest from the list of available wireless networks and connect. No password or additional configuration is necessary. Once connected, open up a web browser and you will be presented with a page to register onto the network. You must enter a valid email address and agree to the terms and conditions before being granted access onto the internet. Notes: When using the university wireless service, some Android devices can only connect to internal websites and not the internet due to an issue with proxy settings on some Android devices. To protect the university only certain activity will be permitted on the wireless network. This includes web browsing and reading emails, but some applications will be blocked. The use of Virtual Private Networks (VPNs) is not allowed. The network connection is unencrypted. More information can be found on the IS website at http://www.nottingham.ac.uk/is/wireless. Hall Facilities Free use of the fitness centre is available to all residential guests. Room keys are asked to be shown at the reception of each facility for access. For further information go to http://www.nottingham.ac.uk/sport/unipark.php. Breakfast will be served from 7.30am until 9.00am on Saturday and from 8.00am until 9.30am on Sunday. The menu (unrestricted amount) is as follows: Grilled Bacon Fried Egg Veggie Grill Preserves Tea Water SCOR 2012 Grilled Pork Sausage Scrambled Egg Grilled Tomato Butter/Flora Coffee Baked Beans Quorn Sausage Toast Cereals - minimum of four choices Fresh Fruit Juice 5 Helpful Telephone Numbers and Emergencies Meals and Entertainment Lunch will be served on all three days of the conference on Friday in вЂњThe Exchange" and during the weekend in the вЂњBusiness School South" (the same buildings where the conference is taking place). Friday Night The dinner will be held at 7.30pm in вЂњFat Cat" (Chapel Quarter, Nottingham, NG1 6JR, see on map). In order to get there you will need to take a bus to the city centre (detailed information on the Trent Barton Website: www.trentbarton.co.uk). The Chapel Quarter is at the far end of the Market Square and at the top of Maid Marion Way. Buses stop at the Market Square. After the dinner social events are planned and this will be a good opportunity for networking. Menu Starters Honey roast butternut squash soup with warm crusty bread Chicken and bacon Caesar salad with herb croutons Creamy garlic mushrooms on sea salt and rosemary toasted foccacia Main Courses Slow cooked short rib of beef, dauphinoise potatoes and buttered greens Baked puff pastry tart filled with melting goats cheese, chargrilled vegetables, sweet balsamic dressed leaves Grilled fillet of lemon pepper hake on a cassoulet of tomatoes, garlic, peppers, beans and spinach Desserts Black Forest Torte with mulled black cherries Chocolate Brownie Sundae Sticky Toffee Pudding with Custard Saturday Night The dinner will be held at 7.30pm in вЂњPeachy Keens" (114 Upper Parliament Street, Nottingham, NG1 6LF, see on map). In order to get there you will need to take a bus to the city centre (one possible option is to take вЂњthe Two" from the вЂњWollaton, Jubilee Campus" bus stop and leave at the вЂњUpper Parliament Street" bus stop). вЂњPeachy Keens" is an all you can eat multi-cuisine buffet. Helpful Telephone Numbers and Emergencies Local Taxi Numbers: DG Cars Trent Cars Nottingham Cars Fast-Lane Cabs (+44) 115 960 7607 (+44) 115 950 5050 (+44) 115 970 0700 (+44) 115 950 1501 SCOR Organiser: Stefan (Chairman) Penny (Vice-Chair) Urszula (Local organiser) (+44) 796 490 8133 (+44) 782 572 9540 (+44) 784 561 4083 Anyone requiring an ambulance should dial 8888 on the internal phone rather than a mobile. The call will be channelled through security who can meet the ambulance and quickly direct them to the scene. If the fire alarm sounds at any time during your stay with us then you must evacuate the building as quickly and safely as possible by the nearest emergency exit. The duty porter for that area will arrive with the Fire Brigade as quickly as possible and will give you further instructions. 6 SCOR 2012 Maps and Floor Plans Maps and Floor Plans SCOR 2012 7 Maps and Floor Plans On Friday we will be based in вЂњThe Exchange" (building no 2) while during the weekend we will be in the вЂњBusiness School South" (building no 7+8). Breakfast is served in вЂњThe Atrium" (building no 5). Woll aton Rd. Western Boulevard A6514 Crown Island Jubilee Campus MAIN ENTRANCE & University of Nottingham Innovation Park (UNIP) 24hr Security Gatehouse Melton Hall PD G Wolla to SC n Ro ad A 609 Ilke ston To city centre Roa d A60 9 uleva ton Bo Middle 1 The Exchange 2 514 rd A6 The Sir Harry & 3 Lady Djanogly Learning Resource Centre To University Park Campus (0.5 miles) Southwell Hall 4 SC The Atrium 5 B The Dearing Building 6 Business School South 7 Auditorium 8 2 2/5/7/11 11 11 3/7 9 11 11 12 Sports Centre Newark Hall SC ay Railw Computer Science Academic schools and departments Centre for English Language Education 10 Contemporary Chinese Studies 10 Computer Science 4 Civil Engineering 13 Education 6/15 International Office 10 Nottingham University 1/7/10/14 Business School Other services Banks/Retail Cafes Faith/Prayer rooms Graduate Centre Libraries Sports Student Services Centre StudentsвЂ™ Union UNIP reception SC Triumph Road Business School North 9 International House 10 11 13 Amenities Building B Nottingham Geospatial Building IPD 12 B National College entrance National College for School Leadership (NCSL) Academic buildings Halls of residence Sir Colin Campbell Building Other services Footpath PD University of Nottingham Innovation Park (UNIP) Sports ground 15 9 Triumph Road PD Pay & Display visitor parking IPD UNIP pay & display visitor parking 6 Triumph Road 14 N Blue-badge parking oad ph R Trium Tennis courts G Gatehouse B Barrier-access control SC Secure cycle parking Hopper bus stop 0 metres 100 Public bus stop Public/Hopper bus stop Pedestrian/cycle route to University Park Campus (0.3 miles) Building public entrances Aspire Sculpture 24-hour ambulance/fire/police (0115) 951 8888 24-hour security contact (0115) 951 3013 8 To University Park Campus (0.5 miles) 08/2011 В© Crown Copyright Licence no. 100030223 De To city centre 00 A62 oad R r by UNITED KINGDOM CHINA MALAYSIA SCOR 2012 Plenary Talks Plenary Talks Gavin Blackett The OR Society About the speaker Following a maths degree from the University of Bath, Gavin started his working career in the Operational Research Executive of British Coal in 1988. In 1992, with a part-time MBA under his belt, Gavin (and the rest of his O.R. colleagues) joined what would become Capgemini, and during his 14 years with the company he worked on O.R. projects in just about every business sector. In 2006 he gave up the consultancy lifestyle for a fixed location when he became Secretary & General Manager at the OR Society. Abstract GavinвЂ™s talk will focus on the benefits of OR Society membership. The OR community needs a strong professional body, and itвЂ™s not always about what it can do for me! Being an active member of the OR Society is all about promoting a healthy subject area and ensuring that it remains vibrant. Critical mass is important for many of the SocietyвЂ™s activities - regional societies, special interest groups and especially accreditation. David Buxton Entrepreneurship in Operational Research - Essential bedfellows? DSE Consulting Ltd. David Buxton has had a varied career history. Starting out as a Geographer before moving into Analytical roles and then into senior positions in general management. Recently, David move into academia, before taking the risky step to strike out and founded dseConsulting. Enjoying commercial success and a reputation as a simulation expert, last year he joined forces to also launch decisionLab, styled as the modern approach to OR consultancy. These business ventures and the previous experiences have each given different insights into the role of OR in business, and had led David to believe that an entrepreneurial spirit in Operational Research is an essential component. Looking at the definition of an entrepreneur: вЂњsomeone who identifies an opportunity and organises, operates and assumes the risk for a business venture to exploit that opportunityвЂњ, it is easy to see that this should be the very essence of OR. However, in practice, we frequently see OR as a вЂ™behind the scenesвЂ™ or supporting function? As evidence of this - given the difference our work can make, and the decisions we work on - wouldnвЂ™t we expect to see some of the high flyers of the business and political worlds coming from an OR background? So why is it that we donвЂ™t? Perhaps we should focus more on risk taking? And what about those characteristics associated with the most successful entrepreneurs: interpersonal skills, the ability to persuade, the ability to lead and motivate, charisma? Are those skills traditionally valued and developed in OR? In the end, does it really matter? Perhaps other disciplines are better suited to the cut and thrust of a commercially-driven world - we can let them take the plaudits whilst we continue with the decision support. But does this threaten to marginalise OR? And in a competitive job-market what can an OR graduate do stand out? Using examples from his own experience, David will highlight the importance of the inner entrepreneur. It hasnвЂ™t all been plainsailing and in this talk David will share his mistakes as well as successes to provide you with insight to help you prepare for your own career and recognise the skills youвЂ™ll need to move seamlessly from academic to commercial to consultancy environments. Tony OвЂ™Connor Chair of the Government Operational Research Service (GORS) Senior Analytical Strategist: Department of Health Former Chief Analyst for the Prime MinisterвЂ™s Delivery Unit Tony has over 25 years experience of OR in Government across Education, Cabinet Office HMT Treasury and since 2009 in the Department of HealthвЂ™s Strategy Group. Worked 15 years in the Dept for Education (in its various guises) manly as an OR analyst, but also in policy, working across a wide range of education policies. Key central Government role was as the Chief Analyst of the Prime MinisterвЂ™s Delivery Unit (2001-2008) where he established a small multi-disciplinary analytical team to improve the use of evidence at the heart of Government, working in particular on performance measurement across all the key indicators underpinning the then GovernmentвЂ™s Public Service Agreements for the Prime Minister. In addition since April 2004 he has been the Chair of GORS representing the interests of all the government OR analysts. He has also been an active member across the wider OR community - regularly attending the OR Soc Conferences, delivering plenary talks in 2008 and 2010. Also Chair of the NATCOR Advisory Board, and member of Heads of OR Forum (HORF) and of the Lancaster Management Science Advisory Board. SCOR 2012 9 Instructions In 2007 he was awarded the CBE in the QueenвЂ™s Birthday Honours for his work promoting Operational Research across Government and his analytical contribution to the Prime MinisterвЂ™s Delivery Unit. In 2010 he was made an OR Companion of Honour by the OR Society Vincent Knight & Louise Orpin OR in Schools Vincent Knight, Cardiff University Vincent Knight is a LANCS lecturer in Operational Research. He is currently chair of the OR in schools taskforce and carries out a wide variety of outreach activities. His research interests are in game theory and queueing theory. Louise Orpin, The OR Society Louise Orpin is the Education Officer at the Operational Research Society. Her role is to raise awareness of OR among young people and their teachers. OR can help encourage young people to continue studying maths by showing them some applications of the maths they are learning and also highlights a potential career for someone who enjoys maths. Abstract Participants in Science, Technology, Engineering and Mathematics (STEM) subjects need to actively encourage and enthuse young school children to explore the various possibilities available to them. Operational Research is no different. In this talk we will present what the OR society already does in means of outreach activities as well as playing a game (audience participation is required) used to introduce game theory to school children. It is hoped that this talk will encourage and enthuse young Operational Researchers to participate in such events and further the great work done by the Society to disseminate the subject. Instructions For Speakers вЂў We ask all speakers to be familiar with the time and the location of their stream and talk, as specified in the conference booklet. вЂў Speakers should arrive at the location of their stream and talk 10 minutes prior to the scheduled start time of the session. вЂў Upon arrival you will be met by the chair of the session. Please introduce yourself and, if applicable, provide the chair with a copy of your presentation to upload onto the seminar room computer. вЂў Each seminar room will contain a computer equipped for Powerpoint and PDF presentations. Please ensure that you are familiar with the equipment before the start of your talk. вЂў Talks are strictly 20 minutes long plus 5 minutes for questions and answers. Anyone going over this time will be asked to stop by the chair. вЂў To aid you with the timing of your presentation, the chair will show the вЂ�time remainingвЂ™ cards when you have 5 minutes and then 1 minute remaining for your presentation. For Chairs вЂў Please arrive at the appropriate seminar room 10 minutes before the start of the stream you will be chairing. You should familiarise yourself with the equipment and ensure there are no obvious problems which would prevent the stream from running to schedule. вЂў In the event of a problem you should immediately seek the help of a local conference organiser. вЂў Delegates presenting in the stream should also be present in the seminar room 10 minutes before the start of the stream. You should introduce yourself to the speakers. They will provide you with electronic copies of their presentations to be loaded onto the seminar room computer. вЂў Uploading presentations: When you arrive at the seminar room you should login to the seminar room computer using the username and password issued to you at registration. You should then upload each speakerвЂ™s presentation onto the desk top ready for the stream to begin. вЂў Your main role will be to ensure that the stream runs to time. The speaker has 20 minutes for presentation followed by 5 minutes of questions and answers. Each talk is followed by a 5 minute break for the comfort of the audience and to allow for movement between streams. 10 SCOR 2012 Smartphone App вЂў If a speaker fails to show for their talk, advise the audience to attend a talk in an alternative seminar room. Please, do not move the next talk forward. вЂў Before each speaker presents, you should introduce them and remind the audience that all interruptions and questions are to be reserved until the scheduled 5 minute question and answer session following each presentation. вЂў During each presentation, please use the вЂ�time remainingвЂ™ cards to indicate to the speaker when 5 minutes and then 1 minute of their presentation remains. вЂў Should a speaker overrun, you must politely but firmly stop their presentation and move on to the question and answer section of the time slot. вЂў After each talk, thank the speaker, encourage applause, and open the floor to questions. Smartphone App SCOR 2012 has gone mobile using Guidebook! We encourage you to download our mobile guide to enhance your experience at SCOR. You will be able to plan your day with a personalised schedule and browse maps and other important information. The free app is compatible with iPhones, iPads, iPod Touches and Android devices. Windows Phone 7 and Blackberry users can access the same information via our mobile site at m.guidebook.com. To get the guide, choose one of the methods below: 1. Download вЂњGuidebook" from the Apple App Store or the Android Marketplace 2. Visit http://guidebook.com/getit from your phoneвЂ™s browser 3. Scan the following image with your mobile phone (QR-Code reader required, e.g. вЂ™Red LaserвЂ™, вЂ™Barcode ScannerвЂ™) The guide can be activated with the Redeem Code вЂњscor2012" under Download Guides. SCOR 2012 11 Conference Sponsors Conference Sponsors The OR Society, www.theorsociety.com Automated Scheduling, Optimisation and Planning (ASAP) research group, University of Nottingham, www.asap.cs.nott.ac.uk 12 SCOR 2012 Conference Sponsors Prospect Recruitment, www.prospect-rec.co.uk Gower Optimal Algorithms Ltd., www.goweralg.co.uk Tata Steel, www.tatasteel.com Banxia Software, www.banxia.com SCOR 2012 13 FREE STUDENT MEMBERSHIP FOR FIRST SIX MONTHS* п‚· п‚· п‚· п‚· п‚· п‚· п‚· п‚· Free access to O.R. Journals and case studies Free O.R. publications Quick literature search Help with O.R. techniques вЂ“ www.theorsociety.com has a selection of learning aids available only to Members. An opportunity to join Regional Societies and Special Interest Groups Access to document repository вЂ“ an online facility to exchange documents, presentations and opinions with other members Help in finding a great job in O.R. вЂ¦and on successful completion of an O.R. based course, Members can apply for CandORS accredited status Share and contribute to the combined knowledge of over 2,500 other O.R. professionals and support other OR Society activities such as marketing the O.R. profession to the business community (www.scienceofbetter.co.uk) and promoting O.R. in schools (www.LearnAboutOR.co,uk) For more details, and to join on-line, visit us at www.theorsociety.com www.theorsociety.com *If you sign up with Direct Debit, payments will start after six months HEREвЂ™S WHAT YOU GET: SCOR Committee SCOR Committee Stefan Ravizza University of Nottingham [email protected] Conference Chair Penny Holborn Cardiff University [email protected] Conference Vice-Chair Michael Clark University of Nottingham [email protected] Emily Cookson Lancaster University [email protected] Magdalena Gajdosz University of Strathclyde [email protected] Pablo Gonzalez Brevis University of Edinburgh [email protected] Izabela Komenda Cardiff University [email protected] Urszula Neuman University of Nottingham [email protected] Martin TakГЎЛ‡c University of Edinburgh [email protected] Alessia Violin Universit Libre de Bruxelles [email protected] SCOR 2012 15 PROGRAMME SCOR 2012 10:00 - 11:00 11:00 - 11:30 11:30 - 12:30 12:30 - 13:30 13:30 - 15:00 15:00 - 15:30 09:00 - 10:30 10:30 - 10:45 10:45 - 11:45 11:45 - 12:00 12:00 - 13:00 13:00 - 14:00 14:00 - 15:30 15:30 - 16:00 16:00 - 17:30 17:30 - 19:30 19:30 - 21:30 12:15 - 13:15 13:15 - 13:30 13:30 - 13:45 13:45 - 14:35 14:35 - 14:45 14:45 - 16:15 16:15 - 16:30 16:30 - 18:00 18:00 - 19:30 19:30 - 22:30 Transport I Graphs/Networks Transport II Supply Chain Management II A26 Supply Chain Management I Multicriteria Decision Analysis I Saturday, 21st April 2012 A24 A25 Optimisation II Heuristics/Metaheuristics I Break Reliability/Risk Assesment Heuristics/Metaheuristics II Coffee Break Plenary Talk: Tony O'Connor (GORS) - A25 Lunch Optimisation III Heuristics/Metaheuristics III Coffee Break Optimisation IV Scheduling/Timetabling I Free Time Dinner @ Peachy Keens Free Time Dinner @ Fat Cat and Social Evening Coffee Break LT2 A08 Multicriteria Decision Analysis II Sunday, 22nd April 2012 A24 A25 A26 Optimisation V Scheduling/Timetabling II Decision Support Coffee Break Plenary Talk: Vincent Knight (Cardiff University) and Louise Orpin (The OR Society) - A25 Lunch Simulation/System Dynamics Optimisation VI Scheduling/Timetabling III Neural Networks/Machine Learning Award and Closing Speech: Stefan Ravizza (SCOR) - A25 Healthcare Stochastic Modelling III Stochastic Modelling II A08 Stochastic Modelling I Friday, 20th April 2012 Welcome Reception and Lunch Welcome Speech: Stefan Ravizza (SCOR) - LT2 Plenary Talk: Gavin Blackett (The OR Society) - LT2 Plenary Talk: David Buxton (DSE Consulting Ltd.) - LT2 Break Mathematical Programming Optimisation I LT1 Programme Overview 17 Friday, April 20, 2012 12:15вЂ“13:15 Welcome Receptions and Lunch 13:15вЂ“13:30 Welcome Speech: Stefan Ravizza (LT2) 13:30вЂ“13:45 Gavin Blackett (The OR Society) (LT2) 13:45вЂ“14:35 David Buxton (DSE Consulting Ltd.) (LT2) 14:35вЂ“14:45 Break 14:45вЂ“16:15 Optimisation I (LT1) Chair: Alessia Violin 1. Comparisons between observable and unobservable M/M/1 queues with respect to optimal customer behaviour Rob Shone, Vincent Knight and Janet Williams 2. Optimization of electricity trading using linear programming Minja MarinoviВґc, Lena ГђordeviВґ ВЇ c, Dragana MakajiВґc-NikoliВґc and Milan StanojeviВґc 3. Performance measurement and trade-offs in UK higher education institutions Carolyn Booker, John Quigley and Lesley Walls 14:45вЂ“16:15 Transport I (LT2) Chair: Penny Holborn 1. Optimal toll enforcements on motorways Elmar Swarat, Guillaume Sagnol and Ralf BorndГ¶rfer 2. The effects of release levels and trajectory lengths on the aircraft arrival sequence Stanislava Armstrong, Jason Atkin, Geert De Maere and Edmund Burke 3. Optimisation of traffic signal settings at arterials during variable conditions Cesar Velandia-Brinez, Ruibin Bai, Graham Kendall and Jason Atkin 16:15вЂ“16:30 Coffee Break 16:30вЂ“18:00 Mathematical Programming (LT1) Chair: Pablo Gonzalez Brevis 1. Nurse rostering in a Danish hospital Jonas Baeklund 2. A bilevel model for valves location in water distribution systems Andrea Peano 3. The primal-dual column generation method: theory and new applications Pablo GonzГЎlez-Brevis, Jacek Gondzio and Pedro Munari 16:30вЂ“18:00 Multicriteria Decision Analysis I (LT2) Chair: Izabela Komenda 1. A nice use for MCDA in public health: potential new approaches to decision making in the national institute for health and clinical excellence Brian Reddy 2. Compromise solutions Kai-Simon Goetzmann, Christina BГјsing, Jannik Matuschke and Sebastian Stiller 3. Lower bound improvements of penalty parameters for discrete - continuous linear bilevel problems Renato Mari 18:00вЂ“19:30 Free Time 19:30вЂ“22:30 Dinner @ Fat Cat and Social Evening 18 SCOR 2012 Saturday, April 21, 2012 09:00вЂ“10:30 Stochastic Modelling I (A08) Chair: Emily Cookson 1. Stabilizing policies for employment portals Hanyi Chen and Burak Buke 2. Assortment planning with substitution effects Jochen Schurr 3. Decomposition techniques for stochastic unit commitment problems Tim Schulze, Andreas Grothey and Kenneth I.M. McKinnon 09:00вЂ“10:30 Optimisation II (A24) Chair: Pablo Gonzalez Brevis 1. The traveling visitor problem and algorithms for solving it Milan Djordjevic, Marko Grgurovic and Andrej Brodnik 2. A dynamic programming heuristic for the quadratic knapsack problem Franklin Djeumou Fomeni and Adam Letchford 3. Compact formulations of the Steiner traveling salesman problem Saeideh D. Nasiri, Adam Letchford and Dirk O. Theis 09:00вЂ“10:30 Heuristics / Metaheuristics I (A25) Chair: Penny Holborn 1. Heuristics for a split vehicle routing problem with backhaul Michela Lai, Massimo Di Francesco and Paola Zuddas 2. Periodical vehicle routing problem due to driver familiarity Matthew Soulby and Jason Atkin 3. Dynamic vehicle routing problems with pickups, deliveries and time windows Penny Holborn, Jonathan Thompson and Rhyd Lewis 09:00вЂ“10:30 Supply Chain Management I (A26) Chair: Magdalena Gajdosz 1. The impact of on time delivery on supply chain management: are third party logistics providers worth the investment? Yolanda Silvera and Rebecca DeCoster 2. Forecasting ARMA demand processes: the impact of temporal aggregation Bahman Rostami Tabar, Mohammad Zied Babai, Aris Syntetos and Yves Ducq 3. The impacts of material convergence on the post-disaster humanitarian logistic operation Nha-Nghi Huynh, Nha-Nghi Huynh, Sandra Transchel, Maria Besiou and Luk Van Wassenhove 10:30вЂ“10:45 Break 10:45вЂ“11:45 Stochastic Modelling II (A08) Chair: Emily Cookson 1. Time-dependent stochastic modelling for ambulance demand prediction and scheduling Julie Williams, Harper Paul, Gillard Jonathan and Knight Vincent 2. Point process models for assessing the reliability of desalination plant equipments subject to failures due to red tide events Ahmed Al Hinai and B. M. Alkali 10:45вЂ“11:45 Reliability / Risk Assessment (A24) Chair: Magdalena Gajdosz 1. Reliability assessment of subsea systems in ultra-deepwater oil and gas developments Anietie Umofia, Stephen Okonji and Shaomin Wu 2. Modelling the impact of human and organisational factors on the safety risk over time Magdalena Gajdosz, Susan Howick and Tim Bedford 10:45вЂ“11:45 Heuristics / Metaheuristics II (A25) Chair: Michael Clark 1. An improved choice function heuristic selection for cross domain heuristic search John Drake and Ender Ozcan 2. Hyper-heuristic to construct magic squares Ahmed Kheiri and Ender Ozcan 10:45вЂ“11:45 Supply Chain Management II (A26) Chair: Alessia Violin 1. Markovian analysis of stochastic serial multi echelon supply chains Despoina Ntio and Michael Vidalis 2. Modeling and evaluating a tandem supply chain with multiple stages Michail Geranios and Michail Vidalis 11:45вЂ“12:00 Coffee Break 12:00вЂ“13:00 Tony OвЂ™Connor (GORS) (A25) 13:00вЂ“14:00 Lunch 14:00вЂ“15:30 Stochastic Modelling III (A08) Chair: Izabela Komenda 1. Hybrid lateral transshipments in multi-item inventory networks Sandra Rauscher and Kevin Glazebrook 2. A chance constrained model for VRPTW with uncertain demands and travel times Pinar Dursun and Erhan BozdaЛ�g 14:00вЂ“15:30 Optimisation III (A24) Chair: Martin Takac 1. Product form of the inverse revisited PГ©ter Tar and IstvГЎn Maros 2. Parallel coordinate descent method for composite objective Martin TakГЎЛ‡c and Peter RichtГЎrik SCOR 2012 19 Saturday, April 21, 2012 14:00вЂ“15:30 Heuristics / Metaheuristics III (A25) Chair: Penny Holborn 1. Evolutionary techniques for an order acceptance problem Simon Thevenin, Nicolas Zufferey and Marino Widmer 2. Meteheuristics for optimal control of discrete systems Lena Djordjevic, Slobodan Antic and Minja Marinovic 3. Simple heuristics for on-line scheduling of operation theatres Nor Aliza Abd Rahmin and Chris N. Potts 14:00вЂ“15:30 Transport II (A26) Chair: Urszula Neuman 1. Vehicle routing with dependent vehicles Edward Kent and Jason Atkin 2. Capacity planning for motorail transportation Pascal Lutter 3. Integration aspects of the gate allocation problem Urszula Neuman, Jason Atkin and Edmund Burke 15:30вЂ“16:00 Coffee Break 16:00вЂ“17:30 Healthcare (A08) Chair: Izabela Komenda 1. Allocating Welsh emergency medical services to maximise survival Leanne Smith, Paul Harper, Vincent Knight, Israel Vieira and Janet Williams 2. Optimising the use of resources within the district nursing service Elizabeth Rowse, Paul Harper, Janet Williams and Mark Smithies 3. Queueing theory accurately models critical care units Izabela Komenda, Jeff Griffiths and Vincent Knight 16:00вЂ“17:30 Optimisation IV (A24) Chair: Emily Cookson 1. Best next sample Sergio Morales Enciso 2. Optimization modeling of distributed energy systems for a smart grid Pedro Crespo Del Granado, Stein W. Wallace and Zhan Pang 3. Air cargo revenue management Emily Cookson, Kevin Glazebrook and Joern Meissner 16:00вЂ“17:30 Scheduling / Timetabling I (A25) Chair: Stefan Ravizza 1. Scheduling games and referees in football: the last song of a Red Hot Chilean Rocker Mario Guajardo, Fernando AlarcГіn and Guillermo DurГЎn 2. Over-constrained airport baggage sorting station assignment problem Amadeo AscГі and Jason Atkin 3. Probabilistic airline reserve crew scheduling model Christopher Bayliss, Jason Atkin and Geert De Maere 16:00вЂ“17:30 Graphs / Networks (A26) Chair: Michael Clark 1. The design of transportation networks: a multi objective model combining equity, efficiency and efficacy Maria Barbati 2. Organization of a public service through the solution of a districting problem Carmela Piccolo and Sabrina Graziano 3. Modelling the uncertainty of data and the robust shortest path Michael Clark and Andrew J. Parkes 17:30вЂ“19:30 Free Time 19:30вЂ“21:30 Dinner @ Peachy Keens 20 SCOR 2012 Sunday, April 22, 2012 10:00вЂ“11:00 Multicriteria Decision Analysis II (A08) Chair: Martin Takac 1. A non-identical parallel machines scheduling problem with multi-objective minimization Jean Respen, Nicolas Zufferey and Edoardo Amaldi 2. Decision analysis for cost effective maintenance of trunk roads Ena Orugbo and Alkali Babakalli 10:00вЂ“11:00 Optimisation V (A24) Chair: Alessia Violin 1. A choice function based hyper-heuristic for multi-objective optimization Mashael Maashi, Graham Kendall and Ender Г–zcan 2. A hybrid encoding scheme for grouping problems Anas Abdalla Osman Elhag and Ender Г–zcan 10:00вЂ“11:00 Scheduling / Timetabling II (A25) Chair: Urszula Neuman 1. An exact algorithm for the uncertain version of parallel and identical machines scheduling problem with interval processing times and total completion time criterion Marcin Siepak 2. Optimizing real-world workforce scheduling problems Nico KyngГ¤s 10:00вЂ“11:00 Decision Support (A26) Chair: Stefan Ravizza 1. Deriving priorities from fuzzy group comparison judgements in the fuzzy analytical network process (FANP) Tarifa Almulhim, Tarifa Almulhim and Ludmil Mikhailov 2. Modelling retail sales for retail price optimization Timo P. Kunz 11:00вЂ“11:30 Coffee Break 11:30вЂ“12:30 Vincent Knight (Cardiff University) and Louise Orpin (The OR Society) (A25) 12:30вЂ“12:30 Lunch 13:30вЂ“15:00 Simulation / System Dynamics (A08) Chair: Magdalena Gajdosz 1. The transition to an energy sufficient economy: a system dynamics model for energy policy evaluation in Nigeria Timothy Mbasuen and Richard C. Darton 2. On the Peter principle: an agent based investigation into the consequential effects of social networks and behavioural factors Angelico Fetta, Paul Harper, Vincent Knight, Israel Vieira and Janet Williams 3. Empirical bayes methods for discrete event simulation Shona Blair, John Quigley and Tim Bedford 13:30вЂ“15:00 Optimisation VI (A24) Chair: Pablo Gonzalez Brevis 1. The k-separator problem Mohamed Sidi Mohamed Ahmed, Walid Ben-Ameur and Jose Neto 2. A multi-dimensional multi-commodity covering problem with application in logistics Alexander Richter, Jannik Matuschke and Felix KГ¶nig 13:30вЂ“15:00 Scheduling / Timetabling III (A25) Chair: Urszula Neuman 1. Flexible mobile workforce scheduling and routing Jose Arturo Castillo Salazar and Dario Landa-Silva 2. A case study of investigating a highly constrained search space Lisa Taylor, Jonathan Thompson and Rhyd Lewis 13:30вЂ“15:00 Neural Networks / Machine Learning (A26) Chair: Martin Takac 1. A meta-parameter analysis of boosting for time series forecasting Devon Barrow and Sven Crone 2. Long-term reserve warranty forecasting with neural network models Shuang Xia and Shaomin Wu 3. Inventory optimization under process flexibility assumption using approximate dynamic programming approaches Mustafa Cimen, Kevin Glazebrook and Christopher Kirkbride 15:00вЂ“15:30 SCOR 2012 Awards and Closing Speech: Stefan Ravizza (A25) 21 ABSTRACTS Abstracts Friday Optimisation I Room: LT1 (14:45 - 16:15) Chair: Alessia Violin 1. Comparisons between observable and unobservable M/M/1 queues with respect to optimal customer behaviour Rob Shone1,в€— , Vincent Knight1 and Janet Williams1 1 Cardiff University; в€— [email protected] It is a well-observed property of queueing systems in which individual behaviour is a factor that customers acting in their own interests do not optimise the collective welfare of society as a whole. In other words, selfish users do not exhibit socially optimal behaviour. In this talk we consider a simple M/M/1 queueing system in which the queue length may or may not be observable by a customer upon entering the system. The вЂњobservableвЂќ and вЂњunobservableвЂќ cases are compared with respect to system properties and performance measures under two different types of optimal customer behaviour, which we refer to as вЂњselfishly optimalвЂќ and вЂњsocially optimalвЂќ. It can be shown that, under both types of optimal customer behaviour, the equality of average queue-joining rates for the observable and unobservable models can be induced by a particular relationship between the system parameters. However, this equality of queue-joining rates results in differences with respect to other performance measures, such as mean waiting times and busy periods. It can also be shown that the two types of model (observable and unobservable) cannot simultaneously share the same selfishly and socially optimal queue-joining rates, regardless of the choice of input parameters. 2. Optimization of electricity trading using linear programming Minja MarinoviВґc1,в€— , Lena ГђordeviВґ ВЇ c1 , Dragana MakajiВґc-NikoliВґc 1 and Milan StanojeviВґc1 1 в€— University of Belgrade, Faculty of Organizational Sciences; [email protected] In last two decades, the liberalization of the electricity markets have been established in order to increase efficiency, harmonize and reduce electricity prices, make a better use of resources, give customers the right to choose their supplier and provide customers with a better service. This change made the electricity market competitive and introduced several new subjects. In this paper, we observe one of the subjects: Electricity Trading Company (ETC) and its daily trading process. We present linear mathematical model of total daily profit maximization subject to flow constraints. It is assumed that the demand and supply are known and some of them are arranged. Possible transmission capacities are known but also additional capacities can be purchased. All trading, transmission prices and amounts are subject of auctions. First, we present energy trading problem as directed multiple-source and multiple-sink network and then model it using linear programming. Also, we provide one realistic example which is slightly changed in order to save confidentiality of the given data. 3. Performance measurement and trade-offs in UK higher education institutions Carolyn Booker1,в€— , John Quigley1 and Lesley Walls1 1 University of Strathclyde; в€— [email protected] The purpose of this research is to examine trade-offs and conflicts between performance measures in the UK Higher Education sector. The performance measures under consideration are those which are imposed on universities from outside, such as statutory performance indicators and newspaper league tables, and which bring rewards in SCOR 2012 the form of either status or funding. The existing literature provides evidence that such measures are causing tension within institutions, but there has to date been no attempt to examine that tension using the tools of management science. The main tool used here is Data Envelopment Analysis. A new DEA model has been developed which extends PodinovskiвЂ™s Tradeoff model to incorporate a weighted preference structure. This model is used first to determine the production possibility set for a group of universities and then to explore the options open to them. In many kinds of performance measurement system the reward achieved by a university, such as a вЂњtop tenвЂќ position or a share of a fixed amount of funding, depends not only on that institutionвЂ™s own decisions but also on the strategic decisions of others. Game Theory provides a range of structures which model such interactive decisions and can aid a decision-maker in determining optimal strategies. The results of the DEA model are therefore processed using a typical league table construction and then evaluated through the lens of Game Theory. Transport I Room: LT2 (14:45 - 16:15) Chair: Penny Holborn 1. Optimal toll enforcements on motorways Elmar Swarat1,в€— , Guillaume Sagnol1 and Ralf BorndГ¶rfer1 1 Zuse Institute Berlin; в€— [email protected] We will present the problem of computing optimal tours of toll inspectors on German motorways. The control is the responsibility of the German Federal Office of Goods Transport (BAG). They are interested in improving the control planning by the use of optimization techniques. We build up an integrated model, consisting of a tour planning and a duty rostering part. The tours should guarantee a network-wide control whose intensity is proportional to given spatial and time dependent traffic distributions. We model this using a spacetime network and formulate the associated optimization problem as a Multi-Commodity Flow Problem in an integer programming (IP) formulation. The rostering part is needed, since we must assign a crew to each tour. All duties of a crew member must fit in a feasible roster. It is also modeled as a Multi-Commodity Flow Problem in a directed acyclic graph, where specific paths correspond to feasible rosters for one month. To the best of our knowledge there is no approach in the literature that integrates vehicle routing and duty rostering (planning) into one model yet, and there is no model of Toll Enforcement Optimization. With our approach all legal rules can be modeled. We present computational results which document the practicability of our proposal. 2. The effects of release levels and trajectory lengths on the aircraft arrival sequence Stanislava Armstrong1,в€— , Jason Atkin1 , Geert De Maere1 and Edmund Burke2 University of Nottingham; в€— [email protected] University of Stirling; 1 In the literature, the arrival sequencing problem is commonly addressed without consideration for the control problem within the stacks, or the control problem between the stacks and the runway. When used at airports like Heathrow, where during busy times aircraft are arranged in stacks and are released predominantly from the bottom level of each stack, such algorithms could lead to solutions that achieve very good objective function values, but are not always feasible in practice. The main goal of this work is to find feasible arrival sequences by considering the sequencing and control problems 23 Abstracts Friday simultaneously. An exact multi-objective dynamical programming algorithm was developed for this purpose. Its effect on the arrival sequence and some potential benefits that can be achieved at Heathrow through slight tactical changes have been investigated. This presentation focuses in particular on the impact which varying the number of release levels has on the arrival sequence, both in terms of runway utilisation and of waiting time per aircraft. Furthermore, we will consider the effects of extending the lengths of the trajectories from the stack to the runway for some of the aircraft. This allows the aircraft that remain in the stacks to ladder down faster into the release levels and as a consequence, may result in better sequences becoming feasible. 3. Optimisation of traffic signal settings at arterials during variable conditions Cesar Velandia-Brinez1,в€— , Ruibin Bai2 , Graham Kendall3 and Jason Atkin4 1 University of Nottingham Ningbo China; [email protected] The University of Nottingham Ningbo China;3 The University of Nottingham Malaysia Campus;4 The University of Nottingham; в€— Effective traffic signal timings are capable of providing unstopped vehicular movements at arterial intersections. However, during peak demand hours, such strategies are unable to provide continuous green indications. They might worsen prevalent traffic conditions if not revised to avoid queue overflows. Signal settings (cycle time, green times, phase sequences and offsets) can be calculated with different objectives in mind. Offsets are used essentially to synchronise signals. It is often considered that progression schemes (maximisation of throughput by co-ordination) are only achievable during light traffic conditions, and the use of other approaches based on minimisation of disutility functions, e.g. delay, number of stops, queue lengths, represent better congested road networks. A critical challenge is the staging of static queues and platoons (incoming groups of vehicles) to avoid progression disruptions and overflowing queues. Therefore, a suitable control method would be able to cope with traffic outbursts, accommodating moving vehicles, and discharging queues regularly. The proposed methodology examines the interactions between platoons and queues, considering both progression and fair allocation of green times. For this purpose, a set of experiments using a traffic micro-simulation are proposed to reproduce scenarios fluctuating between low and high peaks of demand. Measures of effectiveness will be analysed based on progression bandwidth, platoon composition, and queue interactions, while considering side road conditions. Our approach studies this phenomena from the perspective of vehicle groups rather than network or individual performance indicators, which may provide new insights to the problem of finding adequate traffic signal settings at arterial roads. Mathematical Programming Room: LT1 (16:30 - 18:00) Chair: Pablo Gonzalez Brevis 1. Nurse rostering in a Danish hospital Jonas Baeklund1,в€— 1 Aarhus University; в€— [email protected] This presentation will describe a nurse rostering problem from a ward at a Danish hospital. The problem is highly constrained and comprises a large set of different constraints. A branch-and-price method for solving the problem exactly is proposed. The master problem is to assign schedules to the nurses, and its linear relaxation is solved by means of column generation. The pricing sub-problem is to generate feasible schedules for the nurses and вЂ“ as a couple of different 24 constraints including several special Danish regulations have to be observed вЂ“ is solved by constraint programming. A number of specific algorithms for handling these constraints are proposed. The method is very flexible regarding the rules a schedule should comply with, which is a key concern when creating solution methods for nurse rostering problems. Computational tests show that optimal solutions can be found for instances with a two weeks planning period in a reasonable amount of computing time. 2. A bilevel model for valves location in water distribution systems Andrea Peano1,в€— 1 ENDIF - UniversitГ degli Studi di Ferrara; [email protected] Maintenance operations on the pipes of a water distribution system (WDS) require to drain the leaking pipe before repairing. To drain a pipe, some of the isolation valves already present in the network are closed, in such a way that the smallest part of network containing the damaged pipe is disconnected from each of the reservoirs feeding the WDS. In this way, only that subnetwork is isolated and drained. Such subnetworks are called network sectors and their shape is determined by valves positioning. Isolation valves are usually located at the extremes of the pipes. Since valves are expensive, WDSs can be equipped with just a limited number of valves, whose location poses a challenging optimization problem. When any pipe is equally like to require maintenance, the best valve location is the one which minimizes the maximum undelivered demand in case a sector needs to be isolated. Undelivered demand accounts not only for the demand of the sector which requires maintenance, which is drained on purpose, but also of the demand of any other sector which gets disconnected from the reservoirs as a secondary effect of isolating the first sector. This issue makes this real-life problem much more complex than a pure graph partitioning problem. We propose a bilevel mixed-integer linear programming model, where the outer level models valves location and the inner level models water flow. We show how to reformulate the bilevel model as a single level mixed-integer linear model, and test our approach on a real life WDS. в€— 3. The primal-dual column generation method: theory and new applications Pablo GonzГЎlez-Brevis1,в€— , Jacek Gondzio1 and Pedro Munari2 1 University of Edinburgh; [email protected] University of Sao Paulo; In this talk we introduce the primal-dual column generation method. This method relies on well-centred and suboptimal dual solutions to generate new columns in a column generation framework. Theoretical support is provided to show that the method converges to an optimum if such optimum exists. Additionally, computational comparisons with the standard column generation and the analytic centre cutting plane method are presented. The problems on which we have performed the comparisons are the cutting stock problem, the vehicle routing problem with time windows and the capacitated lot sizing problem with setup times. The method shows consistently reductions in the number of outer iterations as well as CPU time when solving the relaxations of these combinatorial optimization problems after applying a Dantzig-Wolfe reformulation. The results are encouraging showing that the method is an attractive general purpose column generation method. Its dynamic adjustable optimality tolerance and its natural stabilization features make it a competitive option in this context. The performance of the method is enhanced when larger instances are considered. в€— SCOR 2012 Abstracts Friday Multicriteria Decision Analysis I Room: LT2 (16:30 - 18:00) the ideal point by a super-ideal reference point. Compromise solutions thus neatly fit with the concept of Pareto optimality. Chair: Izabela Komenda 3. Lower bound improvements of penalty param1. A nice use for MCDA in public health: poten- eters for discrete - continuous linear bilevel probtial new approaches to decision making in the na- lems tional institute for health and clinical excellence Renato Mari1,в€— 1,в€— Brian Reddy 1 в€— UniversitГ di Roma "Tor Vergata"; [email protected] 1 ScHARR, University of Sheffield; в€— [email protected] The National Institute for Health and Clinical Excellence (NICE) is an agency of the NHS, providing guidance to the health services and other relevant decision making bodies in England regarding new drugs and technologies, broader clinical practice and public health. It combines evidence-based and health economic approaches to medicine with equity concerns in order to adequately prioritise interventions, attempting to reduce variations in levels of treatment between local regions and encourage best practice across the health system. However, for a number of reasons it is challenging to adequately quantify, model and describe the multiple effects of public health interventions. As a result there is uncertainty around their cost effectiveness; this adds to the complexity of the decision making process. Multi-criteria decision analysis (MCDA) relates to the methods and procedures by which concerns about multiple conflicting criteria can be formally incorporated into the management process and is used to provide a framework to help decision makers structure complex decisions. Typically these problems would also include multiple ways of judging these criteria, multiple objectives, multiple stakeholders and/or high levels of uncertainty. Such situations are common in public health scenarios. This presentation will describe some of the most common difficulties of measuring cost effectiveness in public health and explain why MCDA techniques may be an appropriate method to overcome some of these issues. It will then explain areas within the Centre for Public Health Excellence in NICE where MCDA approaches are currently being investigated and may be incorporated in the future. Linear bilevel programming problems are the most studied class of bilevel problems and have been widely used to represent real life applications in which there are hierarchical decisional structures. The case in which a subset or all the variables are discrete represents another important class of problems on which we focused as they enable to better describe applications and problems with an inner combinatorial nature. We consider a particular class of linear bilevel problems in which the variables controlled by the leader are required to be discrete. It is a well known result that such a problem is equivalent to a continuous linear bilevel problem in which the integrality requirements are relaxed and the leaderвЂ™s objective function is modified including a concave penalty function weighted by a penalty parameter. This equivalence is true for a sufficiently large value of this parameter. A valid lower bound for it is already known. We provide two improvements of this existing lower bound and experiment the two new lower bounds on a set of 120 test problems. The parameters proposed are better from a theoretical point of view because they assure a reduction of the penalty used to force the integrality requirements on the upper level variables. This improvement is also clearly shown by the computational results: the CPU time spent to solve the problem is on average less than 20% and 30% respectively for the two proposed lower bounds. This implies the possibility to solve larger instances increasing the applicability of bilevel models. 2. Compromise solutions Kai-Simon Goetzmann1,в€— , Christina BГјsing1 , Jannik Matuschke1 and Sebastian Stiller1 1 TU Berlin; в€— [email protected] Applications of combinatorial optimization often feature several contradicting objectives, e.g., cost and duration of a transport. The basic concept in multicriteria optimization is Pareto optimality: a solution is Pareto optimal, if improving one objective is impossible without worsening another. However, in general the number of Pareto optimal solutions is exponential. To choose a single, well-balanced Pareto optimal solution, Yu (1973) proposed compromise solutions. A compromise solution is a feasible solution closest to the ideal point. The ideal point is the component-wise optimum over all feasible solutions in objective space. Compromise solutions are always Pareto optimal. Using different weighted norms, the compromise solution can attain any point in the Pareto set. The latter does not hold for other concepts, e.g., optimization over different weighted sums of objectives. In particular, compromise solutions find well-balanced Pareto solutions that may escape weighted sum methods. Compromise solutions (and the slightly more general reference point methods) are widely used in state-of-the-art software tools. Still, there are very few theoretical results backing up these methods. We establish a strong connection between approximating the Pareto set and approximating compromise solutions. In particular, we show that an approximate Pareto set always contains an approximate compromise solution. The converse is also true if we allow to substitute SCOR 2012 25 Abstracts Saturday Stochastic Modelling I Room: A08 (09:00 - 10:30) Chair: Emily Cookson 1. Stabilizing policies for employment portals Hanyi Chen1,в€— and Burak Buke1 1 University of Edinburgh; в€— [email protected] The portals, which match the people who provide a specific service with the people who demand the service, are becoming increasingly popular recently. In this talk, we concentrate on employment portals, where the employers and employees are assumed to arrive with respect to independent poisson processes with rate О»1 and О»2 respectively. Each given employee can match with a specific employer with probability q independently. This system resembles assembly-like queueing systems. However, with q < 1 it differs significantly from assemblylike systems and has not been studied in the literature. We model it as a two-dimensional Continuous Time Markov Chain and analyze its properties. Our main focus is on stabilizing policies for such portals. To consider the stability of the system, we will first consider the case when the matching probability q = 1, as it can be simplified to an onedimensional birth-death process, which is well-known that the system is null-recurrent when the О»1 = О»2 and transient when О»1 = О»2 . For the case when 0 < q < 1, we will prove that the same conclusion as the case of q = 1 holds. Next, we will introduce the Accept the Shortest Queue policy, which forces constraint on the acceptance of customers. The system will accept employees(employers) only when they have a smaller or equal number than employers(employees). Under this policy, the system is ergodic for any set of arrival rates, but the rate of rejecting customers is exceptionally large. Therefore we consider how to modify it to enable us to accpet more customers without losing stability. 2. Assortment planning with substitution effects Jochen Schurr1,в€— 1 University of Edinburgh; в€— [email protected] The generation unit commitment problem is to find the scheduling of a set of electric power generation units and their power output over a short term planning period вЂ“ typically 24 to 72 hours ahead. In traditional formulations the objective is to minimise the cost for real power output subject to technical constraints such as load balance, spinning reserve and minimum up-and downtimes of individual units. Deterministic variants of this problem are well known and researched and are being solved successfully in the energy industry, mainly due to good predictability of future electricity demand. However, due to increased demand uncertainty and fluctuating wind supplies it becomes more and more important to incorporate uncertainty explicitly in the problem formulation. Stochastic unit commitment problems are large scale multistage mixed integer optimisation programmes which are excruciatingly hard to solve. In this talk I will give an outline of the problem formulation and describe the scenario decomposition techniques we use to make the problem more tractable. Our solver is implemented in C++ and some numerical results are available to underline the importance of decomposition when solving this class of problems. 1 Lancaster University; в€— [email protected] In this talk, we propose an assortment planning heuristic with active learning that accounts for substitution effects. Some subset selection problems on a retail level, arising for example in internet advertising or in the apparel industry, face besides the obvious resource limitation further challenges that are due to high uncertainty in demand. Unlike conventional retailers, fast fashion retailers like Zara or H&M have invested in highly efficient supply chains that enable them to react promptly on additional information or changes in customer preferences. This ability raises the question how one should optimally allocate show room space to products in order to maximize profit over the entire selling season. We present a dynamic programming (DP) approach with Bayesian learning to study assortment decisions in a limited horizon setting. A particular challenge when accounting for substitution effects is the fact that the DP is no longer weakly coupled and hence cannot be decomposed into single-product sub-problems. Further, the Bayesian learning scheme becomes incomparably more complex as compared to existing models that assume independence among products. We will briefly discuss the simplification approach via a one-step look ahead of the DP and a Monte-Carlo integration scheme for the expected cumulated future profits. Further, computational results will be provided that demonstrate the large-scale feasibility and performance of the approach. 3. Decomposition techniques for stochastic unit commitment problems Optimisation II Room: A24 (09:00 - 10:30) Chair: Pablo Gonzalez Brevis 1. The traveling visitor problem and algorithms for solving it Milan Djordjevic1,в€— , Marko Grgurovic1 and Andrej Brodnik1 UP FAMNIT; в€— [email protected] We consider new problem named the Traveling Visitor Problem (TVP). Visitors start from a hotel with desire to visit all interesting sites in a city exactly once and to come back to the hotel. Since, the visitors use streets and pedestrian zones, the goal is to minimize the visitorвЂ™s traveling. A new problem is similar to the Traveling Salesman Problem (TSP) with a difference that the traveling visitors, during its visit of sites, canвЂ™t fly over buildings in the city, instead visitors have to go around these obstacles. That means that all Euclidean distances, like those in Euclidean TSP, are impossible in this case. The tested benchmarks are combined from three real instances made using tourist maps of cities of Venice, Belgrade and Koper and two instances of modified cases from TSPLIB. We introduced and compared two exact methods for solving the TVP. In all tested cases the Koper Algorithm significantly outperforms the NaГЇve Algorithm for solving the TVP - the difference in quality of solutions differs from 6.52% to 354.46%. 1 2. A dynamic programming heuristic for the quadratic knapsack problem Franklin Djeumou Fomeni1,в€— and Adam Letchford1 1 Lancaster University; [email protected] It is well known that the standard (linear) knapsack problem can be solved exactly by dynamic programming in O(nc) time, where n is the number of items and c is the capacity of the knapsack. The quadratic knapsack problem, on the other hand, is NP-hard in the strong sense, which makes it unlikely that it can be solved in pseudo-polynomial time. We show however that the dynamic programming approach to the linear knapsack problem can be modified to yield an effective heuristic for the quadratic version. в€— Tim Schulze1,в€— , Andreas Grothey1 and Kenneth I.M. 3. Compact formulations of the Steiner traveling McKinnon1 salesman problem 26 SCOR 2012 Abstracts Saturday Saeideh D. Nasiri1,в€— , Adam Letchford2 and Dirk O. Theis3 1 STOR-i DTC, Lancaster University; [email protected] Management School, Lancaster University;3 University of Magdeburg; в€— The Steiner Traveling Salesman Problem (STSP) is a variant of the Traveling Salesman Problem (TSP) that is particularly suitable when dealing with sparse networks, such as road networks. The standard integer programming formulation of the STSP has an exponential number of constraints, just like the standard formulation of the TSP. On the other hand, there exist several known compact formulations of the TSP, i.e., formulations with a polynomial number of both variables and constraints. In this study, we present three of these compact formulations specifically the commodity flow formulations and timestage formulations for the TSP and show how they can be adapted to the STSP. We also compare these formulations in terms of the strength of their resulting linear programming relaxation bound. Heuristics / Metaheuristics I Room: A25 (09:00 - 10:30) Chair: Penny Holborn 1. Heuristics for a split vehicle routing problem with backhaul Michela Lai1,в€— , Massimo Di Francesco2 and Paola Zuddas3 1 Department of Mathematics and Computer Science, University of Cagliari; в€— [email protected] Department of Land Engineering, University of Cagliari;3 Department of Mathematics and Computer Science, University of Cagliari; This research addresses a VRP motivated by a real case study. A carrier must serve two type of customers: the importers receive loaded containers from a depot and return empty containers, whereas the exporters receive empty containers and ship loaded containers to the depot. Unlike classical drayage problems, what is original in this vehicle routing problem is the impossibility to separate trucks and containers during customer service and the opportunity to carry more than one container in some trucks. Moreover, according to the carrierвЂ™s policy, importers must be served before exporters, customers may demand more than one container and may be visited more than once. In order to address this special split backhaul problem, we propose a mathematical model based on a node-arc formulation. Nodes represent the depot, importers and exporters. Arcs represent links between nodes, but, due to precedence constraints, arcs from exporters to importers are not considered. Since this problem is NP hard, this research investigates approximate algorithms and, whenever it is possible, compares approximate solutions to exact ones. In this work we propose a two phase approach. In the first phase, we separate importers and exporters and determine separate routes using an efficient metaheuristic. In the second phase, we propose several heuristics to merge these routes. Finally, we compare our solutions to the real decisions of the carrier who has motivated this problem. 2. Periodical vehicle routing problem due to driver familiarity Matthew Soulby1,в€— and Jason Atkin1 1 University of Nottingham; в€— [email protected] Driver familiarity is often of great importance to delivery companies. Not only will familiarity decrease service and travel times, due to knowing the roads, building entrances, delivery points and so on, but the rapport which can be built up between driver and customer also SCOR 2012 has value. When driver learning is applied to the Vehicle Routing Problem (VRP) a trade off occurs between route length and the driver familiarity within the route. To accommodate this, formulations have been applied in the past which group customers that consistently occur in the same route into delivery areas. Determining whether the delivery areas should remain the same over time or be adapted to account for the periodical nature of the orders needs to be considered. For the normal VRP where driver familiarity is ignored the main focus is usually upon the route length, so taking account of the periodical nature and more predictable elements of the stochastic customer demand is of little consequence. Information obtained from the vehicle routing software and consultancy company, Optrak, has allowed for a more accurate, rich representation of the VRP encountered by delivery companies, considering the gain in driver familiarity and the periodical nature of the customer demand. 3. Dynamic vehicle routing problems with pickups, deliveries and time windows Penny Holborn1,в€— , Jonathan Thompson1 and Rhyd Lewis1 Cardiff University; в€— [email protected] To solve the dynamic pickup and delivery problem with time windows (DPDPTW) we are investigating methods embedded in a rolling horizon framework, thus allowing us to view the problem as a series of static ones. Initial research concentrated on the static variant of the problem. We produced several variations of a general heuristic for constructing an initial feasible solution, and used neighbourhood search operators to make improvements. This was extended into an implementation of a Tabu Search heuristic, varying reconstruction heuristics and a Branch and Bound method to improve the results. Analyses have been performed across a range of benchmark datasets, including both clustered and random allocations of pickup and delivery locations. The approaches used give results which are competitive with the state of the art. Our current research is dedicated to solving the dynamic problem, where a time stamp is allocated to each request and the request does not become known to the system until that time. Investigations have been performed to identify when the algorithms should be updated to incorporate the arrival of new requests. Datasets with both varying degrees of urgency and proportion of dynamic requests have been examined along with various different waiting strategies and the design of new evaluation functions. Competitive results have been achieved across a range of benchmark datasets. 1 Supply Chain Management I Room: A26 (09:00 - 10:30) Chair: Magdalena Gajdosz 1. The impact of on time delivery on supply chain management: are third party logistics providers worth the investment? Yolanda Silvera1,в€— and Rebecca DeCoster1 Brunel University, London; в€— [email protected] The purpose of this research is to develop an analytical model as well as a framework for the measurement of performance within supply chain partnerships. Most existing research on supply chain performance incorporates the use of quantitative analysis, but this has been found to not be entirely appropriate when it comes to the area of supplier relationships and supplier performance management. The major focus of this research is on the area of on time delivery, and its effects on the supplier relationship. There has been the misconception that Supply Chain ManagementвЂ™s main focus is on software and systems. It has long been thought that all that is required for an effective supply chain is an investment in technology; it was not felt that there was a requirement to do anything 1 27 Abstracts Saturday as the technology installed will do everything to improve efficiencies. But with new technologies and globalisation of the markets, this way of thinking has been proving to be wrong. The leading scholars in the area of supply chain management have also been emphasising this new reality, when HBR convened a panel of leading thinkers in the field of supply chain management, technology was not the major issue on their minds it was people and relationship management. This paper, through data collected emphasises the relevance and importance of performance measurement in supply chains, especially those indicators affecting on time delivery. Data collected thus far indicates the advantages and disadvantages of third party logistic providers to the on time delivery process. and non priority goods. The objective is to maximise the throughput of high priority goods under capacity restriction. Simulation will be applied to assess the performance of the model. 2. Forecasting ARMA demand processes: the impact of temporal aggregation Julie Williams1,в€— , Harper Paul1 , Gillard Jonathan1 and Knight Vincent1 Bahman Rostami Tabar1,в€— , Mohammad Zied Babai2 , Aris Syntetos3 and Yves Ducq4 1 University of Bordeaux1, Bordeaux Management School(BEM); в€— [email protected] Bordeaux Management School;3 University of Salford;4 University of Bordeaux1; There are many strategies that may be used to reduce the demand variability and thus to improve forecasting performance. An intuitively appealing such strategy is to aggregate demand in lowerfrequency вЂњtime buckets", In this paper, we investigate the impact of non-overlapping temporal aggregation on forecasting performance. We assume that the non-aggregated demand follows an ARMA-type process and a Single Exponential Smoothing (SES) procedure is used to estimate the level of demand. The theoretical forecast errors (both their mean and variance) are derived for the aggregated and nonaggregated demand in order to contrast the relevant forecasting performances. The theoretical analysis is followed by experimentation with real world data. The results indicate that performance improvements achieved through the aggregation strategy are a function of the aggregation level, the smoothing constant value and the process parameter; they also show that for high positive autocorrelation, aggregation does not add any value. 3. The impacts of material convergence on the post-disaster humanitarian logistic operation Nha-Nghi Huynh1,в€— , Sandra Transchel1 , Maria Besiou1 and Luk Van Wassenhove2 1 в€— Kuehne Logistics University; [email protected] INSEAD; Logistics is central to disaster relief and includes activities such as transport, tracking and tracing, warehousing and last-mile-delivery. However, there are crucial differences between the humanitarian and the commercial logistics. One of the differences is that the conditions in which humanitarian relief organizations operate are extremely chaotic and instead of minimizing inventory or transportation costs the objective is rather to minimize lead times for aid items in order to reduce suffer of disaster victims. One of the challenges humanitarian operations are faced with are the so-called unsolicited donations. In-kind donations often do not meet the relief needs of an affected population, but are nevertheless pushed into local warehouses of the disaster areas. During the Haiti earthquake for example, the number of flights to the Port-au-Prince airport increased from 13 up to 100 during the first three days of response. Thus, the airport was faced with serious bottlenecks and unsolicited donations occupied very limited warehouse capacity in the airport. Over the past years the number of research contributions to humanitarian logistics has risen significantly. However, methods of operations research have not yet widely been applied in this field. In this work a queuing model will be presented which illustrates the effects of unsolicited donations on the Haiti relief operation. Aid items are classified into three classes: high, low 28 Stochastic Modelling II Room: A08 (10:45 - 11:45) Chair: Emily Cookson 1. Time-dependent stochastic modelling for ambulance demand prediction and scheduling 1 Cardiff University; в€— [email protected] For patients requesting Emergency Medical Service (EMS) assistance for a life-threatening emergency, the probability of survival is strictly related to the quickness of assistance. As both demand for, and public expectation of, EMS is escalating in the Western world, the provision of an efficient and effective service is a significant challenge for many nations. A particular difficulty for planners is to allocate often limited resources whilst managing increasing demand for services, in a way to ensure high levels of geographical coverage and to improve key performance targets. We are working with the Welsh Ambulance Service Trust (WAST) which is struggling to meet all of its response time targets. Our work considers a novel time series approach to forecasting the daily demand exerted upon WAST using the model-free technique of Singular Spectrum Analysis; and shows that in addition to being more flexible in approach, the predictions generated using this technique compare favourably to forecasts obtained from conventional methods. We progress to use this technique to predict demand at a regional level, and use a range of approximation and numerical time-dependent priority queueing theory techniques to obtain staffing level recommendations. Our research contributes to the ongoing study of time-dependent multi-server queues through developing the techniques to cope with a priority system where life-threatening emergencies are treated with precedence. Ultimately we aim to develop a time-dependent and priority workforce capacity planning tool to optimise ambulance deployment strategies and generate rosters for crew members. 2. Point process models for assessing the reliability of desalination plant equipments subject to failures due to red tide events Ahmed Al Hinai1,в€— and B. M. Alkali1 1 в€— Glasgow Caledonian University; [email protected] This paper investigates the number of failures related to red tide events and other environmental factors on a Reverse Osmosis (RO) Desalination Plant in Oman. There are clear indications of worsen seawater quality during periods of red tides in the Sultanate of Oman. In this study a failure mode and effect analysis (FMEA) is conducted on the critical equipment in the Plant to identify the classes of failure modes and their effects on the RO Plant smooth operation. The failure and maintenance history data for the period 2006-2010 is evaluated and more emphasis is focused on plant failures during the periods of the Red tide incidents. A stochastic point process model is considered for reliability analysis in this study. The history of the observed failure process is assumed to follow a non-homogenous Poisson process, as the inter-arrival times between the PlantвЂ™s failures vary with time. A standard statistical approach is used for reliability analysis by fitting the Weibull distribution to the data sets. The results obtained are presented on a distribution overview. SCOR 2012 Abstracts Saturday The results presented here is to set a pace of further reliability modelling to schedule cost effective preventive maintenance actions on the RO Desalination Plant equipment. Reliability / Risk Assessment Room: A24 (10:45 - 11:45) Chair: Magdalena Gajdosz used for post-mortem accident analysis and safety risk assessment. This is accomplished by applying it to the analysis of accident reports from hazardous industries and by performing a safety risk study for an external organisation. A mixed-modelling approach, combining system dynamics and methods used in the risk and reliability field (e.g. fault tree analysis that is used to model equipment reliability) has been adopted. The output will be a set of guidelines that can support risk analysts in their future risk studies. 1. Reliability assessment of subsea systems in ultra-deepwater oil and gas developments Anietie Umofia1,в€— , Stephen Okonji1 and Shaomin Wu1 1 Cranfield University; в€— [email protected] The exploration and production of oil and gas is globally witnessing a very dramatic and rapid expansion into deep waters. Studies indicate that deep water fields account for more than 25% of operator investments in offshore facilities and will rise to over 40% by the end of the decade. This drive introduces a significant increase in the cost of hydrocarbon search and also presents unprecedented challenges. The challenges include safety, environment, flow assurance and equipment reliability. Deepwater conditions inherently dictate the development of these fields by means of subsea production systems since traditional surface facilities such as steel-piled jacket might be either technically unfeasible or uneconomical due to the water depth. Maintaining systems located in the ultra deep-water requires specialised and expensive vessels, which need to be equipped with robotic devices due to the water depths. Any requirement to intervene or repair an installed subsea system is thus normally very expensive and may result in considerable economic production loss. High equipment reliability is therefore required in order to safeguard the environment and personnel, and to make the exploitation of hydrocarbons with subsea technology economically feasible. This paper investigates reliability assessment for subsea systems operated in the ultra-deepwater. With API 17N as a key focus, the paper looks at the control system for this type of developments and the reliability assessment. 2. Modelling the impact of human and organisational factors on the safety risk over time Magdalena Gajdosz1,в€— , Susan Howick1 and Tim Bedford1 1 в€— Heuristics / Metaheuristics II Room: A25 (10:45 - 11:45) 1. An improved choice function heuristic selection for cross domain heuristic search John Drake1,в€— and Ender Ozcan1 1 SCOR 2012 University of Nottingham; в€— [email protected] Hyper-heuristics are a class of high-level search technologies which aim to solve computationally difficult problems. Unlike traditional meta-heuristic techniques, a hyper-heuristic operates on a search space of heuristics rather than directly on the search space of solutions. A single-point based search selection hyper-heuristic framework relies on two key components, a heuristic selection method and a move acceptance method. Operating on a single candidate solution until some termination criteria is met, low-level heuristics are repeatedly selected and applied producing a new solution, then a decision is made as to whether to accept this new solution or not. The Choice Function is an elegant heuristic selection method which scores heuristics based on a combination of three different measures and applies the heuristic with the highest rank. Each of these measures are weighted appropriately to provide sufficient intensification and diversification of the heuristic search process. Different methods in the literature have been proposed to manage these weightings, here we will describe a new method loosely based on reinforcement learning. Using the HyFlex software benchmark framework developed to support CHeSC 2011 (the first Cross-domain Heuristic Search Challenge) we have tested and compared this new method for controlling such parameters to previous approaches. 2. Hyper-heuristic to construct magic squares University of Strathclyde; [email protected] This research project is concerned with the analysis and management of safety risks associated with the operation of hazardous systems such as those used in nuclear power plants, chemical plants or transportation organisations. Overall, there are two types of analyses that inform safety risk management of hazardous systems: safety risk assessment and postmortem accident analysis. The review of the literature suggests that the methods currently used in these analyses need to be extended to account for more recent understandings of the impact of people who operate, maintain and control these systems. Also, most of the methods are static, sequential and usually ignore feedback structures within which human decision-making operate. Thus, they are not robust enough to capture the dynamic impact of human and organisational factors on the safety risk. A system dynamics approach, which has been used to analyse feedback systems and their behaviour over time, provides a range of structures that can help to overcome these problems. This research investigates how system dynamics can complement methods traditionally Chair: Michael Clark Ahmed Kheiri1,в€— and Ender Ozcan1 1 University of Nottingham; в€— [email protected] A magic square is a square matrix that contains distinct numbers in which the summation of the numbers in each row, column and the two diagonals has the same constant total known as the magic number. Constructing the magic square has been considered as a hard computational problem domain. A class of hyper-heuristics aims to provide solution across a range of problem domains by selecting and/or mixing a fixed set of low level heuristics during the search process. There has been a growing interest in the development of such general methodologies which searches the space of heuristics rather than the space of the solutions. This study presents a methodology to construct magic squares using a selection hyper-heuristic based on a random descent heuristic selection method. The results show that the approach could be an effective methodology to construct magic squares. The results will be reported in more details at the conference. 29 Abstracts Saturday Supply Chain Management II Sandra Rauscher1,в€— and Kevin Glazebrook1 1 Room: A26 (10:45 - 11:45) Chair: Alessia Violin 1. Markovian analysis of stochastic serial multi echelon supply chains Despoina Ntio1,в€— and Michael Vidalis1 1 University of the Aegean Chios Greece; в€— [email protected] In this project the performance of stochastic serial multi echelon inventory systems is being analyzed. In contrast to my previous work and other similar works, in this case a more complex inventory model with four stages is developed. Furthermore, the Erlang distribution allows the model to depict the replenishment process in a better way compared to other methods that have been utilized in the past. This extended model combined with the two and three stage inventory systems leads to the construction of a framework for the inventory decision making process. Specifically, three serial inventory systems with two, three and four stage respectively have been researched. The demand and the replenishment process are stochastic. Orders follow (S,s) policy. The replenishment processes follow the Erlang distribution. The external demand is distributed by pure Poisson process which means that the amount that each customer asks is one unit. Last but not least the last upstream node is always considered saturated. The supply networks are modeled as continuous Markov processes with discrete states. The structures of the transition matrices of those systems are explored and computational algorithms are developed to generate them for different values of systems parameters. Mat lab software is used for any computation. Various performance measures derive from steady state probabilities such as fill rate, average inventory in systems and cycle time. 2. Modeling and evaluating a tandem supply chain with multiple stages Michail Geranios1,в€— and Michail Vidalis1 1 University of Aegean; в€— [email protected] In this work a serial supply chain with an arbitrary number of nodes (retailer, wholesaler, manufacturer, supplier, etc.) is examined. Each node supplies only one downstream node and is replenished by only one upstream node. Each node, except for the most upstream, faces supply uncertainty and the last node (retailer) additionally faces external demand that follows the pure Poisson distribution. Each node,except for the most upstream, which is saturated- follows a continuous review ordering policy. If the upstream has insufficient stock, then the orders are partially satisfied and the rest is lost. The systemвЂ™s performance is determined by performance measures, such as Fill Rate, Average Inventory. To calculate these measures the supply chain is modeled as a continuous time Markov process with discrete states. Our major task is to figure out how the performance measures are influenced when we expand our system, adding one node at a time. A computational algorithm is developed to generate the transition matrices (different values of system characteristics) and by them the stationary probability distribution. The proposed algorithm is used as an optimization tool to determine the optimal values of the systemвЂ™s parameters. After determining the performance measures, we compare the numerical results in order to reveal the optimal ordering policy. Stochastic Modelling III Room: A08 (14:00 - 15:30) Chair: Izabela Komenda 1. Hybrid lateral transshipments in multi-item inventory networks 30 Lancaster University Management School; [email protected] Saving costs in inventory systems can often only be accomplished by reducing service levels. Allowing lateral transshipments in multilocation inventory networks permits lower levels of safety stock thereby cutting costs while maintaining or improving service levels. Usually, such movements of stock are either carried out in a reactive manner responding to a stock-out in the system, or preventively to rebalance inventory levels. Recent results show that using a hybrid version of these two approaches can yield further improvements. This lies in the fact that shipment costs in many cases consist of a higher fixed and a lower variable part. The rebalancing of inventory levels can thus be achieved at an often negligible additional cost if a reactive transshipment is made. We extend this idea and implement it in a multi-item setup. Our model describes a multi-location inventory network facing compound, non-homogeneous Poisson demand. Instances of demand have an underlying discrete, multivariate distribution. We derive a quasi-myopic policy by applying a dynamic programming policy improvement step to a no-transshipment policy. Transshipment costs are modelled with a knapsack-like structure to accommodate different types of items. We carry out an extensive simulation study to show the benefit of modelling multi-item transshipments against operating single item models in parallel. в€— 2. A chance constrained model for VRPTW with uncertain demands and travel times Pinar Dursun1,в€— and Erhan BozdaЛ�g2 1 Istanbul Technical University Department of Industrial Engineering; [email protected] Istanbul Technical University; In this study a model is developed to solve the vehicle routing problem with time windows (VRPTW) with uncertain demands and travel times. Although the distances are discrete between two nodes, the travel times may not be discrete because the traffic has uncertain nature. It is important to delivery order to customers in specified time window, so handling the uncertainty is more critical. Also the vehicles are capacitated so they must be loaded below their capacity. Chance constrained model based random key represented genetic algorithm is developed and numerical experiments are solved to show effectiveness of the proposed algorithm. в€— Optimisation III Room: A24 (14:00 - 15:30) Chair: Martin Takac 1. Product form of the inverse revisited PГ©ter Tar1,в€— and IstvГЎn Maros1 University of Pannonia; в€— [email protected] Using the simplex method is one of the most effective ways to solve linear optimization problems. The efficiency of the solver procedure is crucial for solving large-scale problems. The solution is obtained by an iterative procedure, where each iteration can be represented by a basis of the linear equation system. During an iteration some vectors must be multiplied by the inverse of the actual basis. In order to speed up these operations, proper basis handling procedures must be applied. Two methodologies exist in the state-of-the-art literature, the product form of the inverse (PFI) and LU factorization. The majority of the LU methods is widely used, because 120-150 iterations can be done without the need of re-factorization, and the PFI can serve about 30-60 iteration without re-inversion in order to provide numerical stability. In our work we revisited the PFI and implemented it in such a way that hundreds or sometimes even few thousands of iterations can be done 1 SCOR 2012 Abstracts Saturday without losing accuracy. The novelty of our approach is in the processing of the non-triangular part of the basis, based on block triangularization algorithms. The resulting inverse of the modified algorithm performs way better than those found in the literature. These results can shed new light on the usefulness of the PFI. вЂњThis publication/research has been supported by the TГЃMOP4.2.2/B-10/1-2010-0025 project.вЂќ 2. Parallel coordinate descent method for composite objective Martin TakГЎЛ‡c1,в€— and Peter RichtГЎrik1 1 The University of Edinburgh; в€— [email protected] In this work we show that randomized block (coordinate) descent methods can be accelerated by parallelization when applied to the problem of minimizing the sum of a semi-separable smooth convex function and a simple block-separable convex function. The speedup, as compared to the serial method, and referring to the number of iterations needed to approximately solve the problem with high probability, is equal to the product of the number of processors and a natural and easily computable measure of separability of the smooth component of the objective function. In the worst case, when no degree of separability is present, there is no speedup; in the best case, when the problem is separable, the speedup is equal to the number of processors. Our analysis also works in the mode when the number of blocks being updated at each iteration is random, which allows for modeling situations with variable (busy or unreliable) number of processors. Heuristics / Metaheuristics III Room: A25 (14:00 - 15:30) Chair: Penny Holborn 1. Evolutionary techniques for an order acceptance problem Simon Thevenin1,в€— , Nicolas Zufferey1 and Marino Widmer2 The problem of the optimal control of discrete systems occurs in many areas and includes a large number of subproblems. The approach analyzed in this paper is grounded on a dynamic model of decision making, developed in spreadsheet environment, with clearly separated tables representing discrete controlled object: (1) the law of dynamics, (2) control space and (3) performance criterion. Discrete processes with different values of the performance criteria are obtained by varying of values of control variables. It is necessary to find the discrete process that gives the minimum value to the performance criterion. In this paper, we also develop metaheuristic method for solving described problem, which are based on tabu search and variable neighborhood search. Two well-known methods have been adapted and implemented in accordance with the described problem, in order to compare obtained results. An implementation of the methods are realized in Visual Basic for Application and combine with some results of a simulation model in Excel spreadsheet. 3. Simple heuristics for on-line scheduling of operation theatres Nor Aliza Abd Rahmin1,в€— and Chris N. Potts1 University of Southampton; в€— [email protected] A hospital is an institution for health care that treats patients with specialized staff and equipment. If we focus on the medical facilities of the hospital, operating theatres form one of the most important and expensive resources. Therefore, surgery is a critical process in a hospital, not only for the cost but also for the impact of a patientвЂ™s health and quality perception. Disruptions of various types can prevent a previously constructed plan from being executed. Waiting for treatment due to operating theatre unavailability can result in deteriorating health and even worse can lead to death. In this paper, we focused on an operating theatre scheduling problem for emergency and regular patients. However, long operation times or a high number of emergency patients arriving can lead to a disruption of previous bookings. We consider an on-line version of this problem where each day a new schedule is created based on current information such as new patients who need to be booked into a slot in the operating theatre and previously scheduled patients whose treatment could not be performed because of operating theatre capacity constraints. We allocate the patients depend on their urgency using a simple heuristic method, updating the schedule every day. Computational results are reported. 1 1 HEC, University of Geneva; [email protected] DIUF Decision Support & Operations Research, University of Fribourg, Switzerland; в€— We consider the order acceptance and scheduling problem, in a single machine environment, with setups, and regular (i.e. not decreasing) objective functions. Order acceptance problem is particularly relevant in a make-to-order production environment, it has gained increasing popularity these last decades. Given a set of n jobs, the problem is to decide which jobs to accept, and to schedule them. The objective is to minimize the penalties brought by rejected jobs and the cost associated with performed jobs. The problem is NP-Hard and there only exists an exact method. We propose to tackle it with heuristics. We present and compare local search methods with population based algorithms for the problem. The local search is a tabu search approach which includes restriction and diversification procedures. Two evolutionary strategies are proposed, a genetic algorithm with local search and an adaptive memory algorithm. Tests are performed using realistic instances and show that the proposed heuristics are very competitive. 2. Meteheuristics for optimal control of discrete systems Lena Djordjevic1,в€— , Slobodan Antic1 and Minja Marinovic1 1 в€— Faculty of Organizational Sciences; [email protected] SCOR 2012 Transport II Room: A26 (14:00 - 15:30) Chair: Urszula Neuman 1. Vehicle routing with dependent vehicles Edward Kent1,в€— and Jason Atkin1 University of Nottingham; в€— [email protected] The vehicle routing problem has been studied extensively throughout academia, and many solution methods have been produced that generate a number of independent routes for vehicles. We have been working with Optrak (a vehicle routing software and consultancy company), and using real world data. Extra constraints arise from these richer problems, resulting in vehicle routing problems that require consideration of the dependencies between vehicles. In particular, when product mixing rules are applied to the demanded products and time windows are applied to these customers, more than one vehicle may be needed to service the customer in a small space of time. Products that canвЂ™t be mixed may need to be delivered at almost the same time for the benefit of the customer. Loading limitations at customers and depots may also present extra constraints that limit the number of vehicles that can be at a depot or a customer at one time. Other real world constraints include routes between customers which may contain tunnels, causing vehicles to have to deliver hazardous goods first before they can pass. A fully loaded vehicle that contains hazardous 1 31 Abstracts Saturday goods would then have to make other stops first, potentially causing other dependent vehicles to have to wait. Together, these constraints may create narrow time windows which need to be met. Thus, some conventional assumptions, such as the single route per customer and the independence of vehicles no longer apply. 2. Capacity planning for motorail transportation Pascal Lutter1,в€— Ruhr University Bochum; в€— [email protected] Loading cars and motorbikes on trains is a challenging task for motorail companies. Several MILP models exist to load containers on trains. Although the general model structure is similar, motorail train loading differs strongly from container loading regarding certain technical requirements. In contrast to recent work on auto-carrier loading we consider route specific requirements and physical constraints in more detail and additionally focus on order acceptance in a dynamic environment. Particularly the integration of the booking process distinguishes our approach from previous ones. Orders are placed at different points of time and must be accepted or rejected immediately so the problem has to be solved repeatedly with varying information. Optimal train utilization can be achieved by the suggested MILP model if vehicle specifications are exactly known. During the booking process decisions have to be made immediately for every arriving booking request. In practice, the frequent use of an optimization model is impossible because of long runtimes and missing the integration in current booking systems. Hence, it is necessary to identify risks and chances in advance to control available capacity. We propose a mixed-integer linear programming model which determines maximum weights for all possible vehicle specifications to optimally decide about the acceptance of orders. We compare our new approach with a simple heuristic method by a simulation study. The proposed models can be solved using standard commercial software as well as open source software and their performance is evaluated. 1 Leanne Smith1,в€— , Paul Harper1 , Vincent Knight1 , Israel Vieira1 and Janet Williams1 1 Response time targets for the Welsh Ambulance Service NHS Trust (WAST) are not currently being met. In particular, the more rural areas in South East Wales consistently perform poorly with respect to the target of reaching 65% of the highest priority emergency calls (category A) within 8 minutes, and are amongst the worst in the UK. This research is concerned with developing mathematical models for the ambulance service system, utilising methods drawn from location theory, to help WAST make better decisions on locations, capacities and deployments. Findings from a developed location/allocation optimisation model, the Maximal Expected Survival Location Model for Heterogeneous Patients (MESLMHP), will be used to suggest suitable allocations of vehicles at stations across the South East region (and subsequently for other areas of Wales), with the aim of maximising the overall expected survival probability of patients given a homogeneous or heterogeneous fleet. The model can incorporate both survival functions and response time targets allowing for different emergency categories to be considered. The model will be run under various scenarios of interest to WAST; changes will be made to the demand of calls, number of available vehicles and shift patterns to see the impact on the expected number of survivors. The allocation obtained may also be used as input to a detailed discrete event simulation. Recommendations will be made to the Trust to help provide a more efficient and effective ambulance service to their population, and to achieve the targets as set by the Welsh Assembly Government. 2. Optimising the use of resources within the district nursing service Elizabeth Rowse1,в€— , Paul Harper1 , Janet Williams1 and Mark Smithies1 1 3. Integration aspects of the gate allocation problem Urszula Neuman1,в€— , Jason Atkin1 and Edmund Burke2 University of Nottingham; в€— [email protected] University of Stirling; Smooth and punctual operation is a priority for most airports in the world. The better the operation, the easier it is for an airport to attract airlines and, in this way, increase the number of passengers. Competition between airports is often not observed directly by passengers, but it exists, is observed by airlines, and can be fierce in some regions. Many aspects of airport operations (e.g. runway sequencing, taxiing, gate allocation) are currently managed in isolation, i.e. without considering the effects of decisions upon other aspects. This is likely to reduce efficiency of an airport as a whole. Integration of these various aspects could potentially improve airport operations. Obviously, integrating runway sequencing with taxiing would reduce the time that an aircraft needs before taking off (after leaving a gate) and to get to a gate (after landing). Way in which the gate allocation process could be improved to aid these two processes will be discussed, along with the difficulties which occur in the integration process and how integration may contribute to smooth airport operations. 1 Healthcare Room: A08 (16:00 - 17:30) Chair: Izabela Komenda 1. Allocating Welsh emergency medical services to maximise survival 32 Cardiff University; в€— [email protected] Cardiff University; в€— [email protected] Recent statements from the UK government indicate that future provision of services within the National Health Service will involve the transition of care from hospitals into the community. District nurses play an important role in caring for housebound patients whilst alleviating some pressure on other primary care services. An increase in the number and complexity of patientsвЂ™ needs treated within the community, coupled with the predicted decline in the number of district nurses poses a potential supply and demand problem. Working closely with a district nursing service in Wales, the optimal size and skill mix of district nursing teams to meet patient demand is investigated. A two-stage model is developed that uses Monte Carlo simulation to generate patient demand, and Linear Programming to find an optimal team composition that meets this patient demand at minimum cost. This approach, novel to workforce planning in the district nursing service, gives results that indicate significant cost savings if district nursing teams are restructured for optimal skill mix. 3. Queueing theory accurately models critical care units Izabela Komenda1,в€— , Jeff Griffiths1 and Vincent Knight1 1 Cardiff University; в€— [email protected] Random number of arrivals and random length of stay make the number of patients in a Critical Care Unit (CCU) behave as a stochastic process. This makes the determination of the optimum size of the bed capacity very difficult. The number of admissions per day, length of stay and bed occupancy are key control parameters to find the optimal number of beds required. In this study queueing theory is used to develop a new mathematical model of patientsвЂ™ flow and is applied to two CCUs in hospitals from the same Health Board. Predictions SCOR 2012 Abstracts Saturday from the model are compared to observed performance of the Units, and the sensitivity of the model to changes in Unit size is explored. The model is also used to analyse the effect of transferring patients and beds from one hospital to another. We conclude that cooperation between both hospitals helps to achieve lower utilisation rates with a smaller probability of rejection. and medium size battery. The outcome of this research will provide an insight on how to handle peak demands with unexpected low wind generation at lowest possible cost. The OR viewpoint of this research aims to shed new light into the design of energy systems for the future. 3. Air cargo revenue management Emily Cookson1,в€— , Kevin Glazebrook1 and Joern Meissner2 Optimisation IV 1 Room: A24 (16:00 - 17:30) Chair: Emily Cookson 1. Best next sample Sergio Morales Enciso1,в€— 1 в€— The University of Warwick; [email protected] We consider the scenario of a memoryless market to sell one product, where a customerвЂ™s probability to actually buy the product depends on the price. We would like to set the price for each customer in a way that maximizes our overall revenue. In this case, an exploration vs exploitation problem arises. If we explore customer response to different prices, we get a pretty good idea of what customers are willing to pay. On the other hand, this comes at the cost of losing a customer (when we set the price too high) or selling the product too cheap (when we set the price too low). The goal is to infer the true underlying probability curve as a function of the price (market behaviour) while simultaneously maximizing the revenue. This paper focuses on learning the underlying market characteristics with as few data samples as possible, exploiting the knowledge gained from both exploring potentially profitable areas with high uncertainty and optimizing the trade-off between knowledge gained and revenue exploitation. The response variable being binary by nature, classification methods such as logistic regression and Gaussian processes are explored. This makes the analytic calculations intractable, so a series of approximations are used, while the knowledge gain optimization is approximated by a dynamic program. A series of simulations of the evolution of the proposed model and a statistical analysis are finally presented to summarize the results. в€— Lancaster University; [email protected] Kuehne Logistics University; The air cargo industry faces some unique challenges: Highly volatile demand, weight/volume uncertainty through variable tendering, and short booking cycles are some of the features. In the case of mixed air carriers, the prioritisation of passengers and their baggage further challenges the allocation of aircraft belly space. Our research considers these challenges and focuses on modelling a new dynamic programming formulation that an air cargo company could use to maximise its expected profit. In particular, the formulation differs from previous ones in that capacity and demand uncertainty is incorporated into the model using probability distributions. The main focus is on spot-sale bookings, making acceptance decisions using dynamic prices formulated under uncertainty. The initial results suggest this dynamic model may give significant improvement over static models. The research is being conducted in collaboration with the cargo division of a major airline. Data analysis has produced interesting results that have been incorporated into the model. Scheduling / Timetabling I Room: A25 (16:00 - 17:30) Chair: Stefan Ravizza 1. Scheduling games and referees in football: the last song of a Red Hot Chilean Rocker Mario Guajardo1,в€— , Fernando AlarcГіn2 and Guillermo DurГЎn3 1 2. Optimization modeling of distributed energy systems for a smart grid Pedro Crespo Del Granado1,в€— , Stein W. Wallace1 and Zhan Pang1 1 в€— Lancaster University; [email protected] UKвЂ™s decarbonisation policies are increasing the share of renewable resources in the energy generation mix to 20-30%. Wind power will deliver most of the renewable output by 2020. Due to uncertainty in availability of wind generation, this new energy mix creates new planning challenges to maintain a stable and reliable supply-demand balance. From an OR perspective, this research focuses on modeling the flexibility and robustness of the energy infrastructure in the presence of short term extreme events. Through a bottom-up approach the research is an understanding of how synergies of generating units work in sub-energy systems, such as a house, or small communities. Which combination of energy generation will cope with high wind energy input? Through a dynamic portfolio optimization model, we assessed the energy mix for a typical UK house to understand the value of storage. We observed that battery storage in households can shift house peak demands to less stressful periods for the grid. Results showed a 20-25% energy cost saving for end users. We also have modeled the energy mix of a small community (University Campus) in the form of a stochastic optimization model that considers wind generation, CHP, SCOR 2012 NHH Norwegian School of Economics and Business Administration; в€— [email protected] University of Chile;3 University of Chile, University of Buenos Aires; The use of sports scheduling in the Chilean football has run for years, as a result of collaboration between managers of the Football Association and researchers in OR. The problems in the project include the scheduling of games of several tournaments and the assignment of referees to the games. As part of the research group, in this talk I will present an overview of the achievements of the project and I will detail our most recent work on the referee assignment problem. Given a schedule of games, the problem consists of assigning referees to the games, fulfilling a number of operational and fairness constraints. We propose an integer programming model, whose natural formulation can be solved by using standard solvers. However, large instances may lead to relatively long solution times, an undesirable matter for practical use. We propose a two-stages solution approach based on patterns. Firstly, we generate the patterns for each referee by solving an IP model that considers some constraints of the problem. The patterns indicate the set of games to which a referee can be assigned in each round. Secondly, we implement another IP model that incorporates the remaining constraints and assigns the referees to the games. With this approach, we reduce the solution time significantly. To our knowledge, this is the first work proposing a pattern approach for referee assignment. Moreover, while the scheduling of games has recently shown a massive development, the literature of sports scheduling applied to real-world referee assignment problems is still scarce. 33 Abstracts Saturday 2. Over-constrained airport baggage sorting station assignment problem Amadeo AscГі1,в€— and Jason Atkin1 1 University of Nottingham; в€— [email protected] Correct assignment of airport resources can greatly affect the quality of service which airlines and airports provide to their customers. Good assignments can help airlines and airports to keep to published schedules, by minimising changes in these schedules and reducing delays. Given the expected increases in civil air traffic, the complexities of resource scheduling and assignment continue to increase. For this reason, as well as the dynamic nature of the problems, scheduling and assignment are becoming increasingly difficult. The assignment of Baggage Sorting Stations to flights is one of the resource assignment problems in an airport, and like many other real world optimisation problems, it naturally has several objectives, which conflict with each other. We present a model for the problem, look at different approaches for obtaining good solutions and study these to gain an insight into their qualities. A network design problem consists in locating facilities (nodes and arcs) that enables the transfer of flows (passengers and/or goods) from given origin-destination pairs. The topic can have several applications within transportation and logistics contexts. As various criteria can be assumed as objective functions, the problem can be formulated through multi-objective models. In the literature of multi-objective network design problems two fundamental bi-objective models can be emphasized: the Maximum Covering Shortest Path (MCSP) model and the Median Shortest Path (MSP) model. Both the models determine paths on a network considering a trade off between a measure of efficiency (the path length) and a measure of attractiveness (the coverage and the usersвЂ™ distance). In this work we propose multi-objective models in which also balancing or equity aspects, i.e. measures of the distribution of distances of users from the path, are considered. These kinds of models can be used when there is the need to balance risks or benefits among all the potential users deriving from the location of the path to be designed. In particular we illustrate bi-objective models whose optimization criteria are similar to the MCSP and MSP objectives, but including a certain balancing measure as constraint. The application of the proposed models to a benchmark problem used in literature to test these kinds of models, show that they are able to find Pareto solutions characterized by significant level of equity. 3. Probabilistic airline reserve crew scheduling 2. Organization of a public service through the model solution of a districting problem Christopher Bayliss1,в€— , Jason Atkin1 and Geert De Carmela Piccolo1,в€— and Sabrina Graziano1 Maere1 1 University of Nottingham; в€— [email protected] This paper introduces a probabilistic model for airline reserve crew scheduling. The model can be applied to any schedules which consist of a stream of departures from a single airport. Reserve crew demand can be captured by a single probability (probability of crew absence) for each departure. The aim of our model is to assign some fixed number of available reserve crew in such a way that the overall probability of crew unavailability in an uncertain operating environment is minimised. A comparison of different probabilistic objective functions, in terms of the most desirable simulation results, is carried out, complete with an interpretation of the results. Based on the best objective function, a sample of heuristic solution methods are tested and compared to the optimal solutions on a set of problem instances. The current model can be applied in the early planning phase of reserve scheduling, when very little information is known about crew absence related disruptions. The main conclusions include the finding that the probabilistic objective function approach gives solutions whose objective values correlate strongly with the results that these solutions will get on average in repeat simulations. Minimisation of the sum of the probabilities of crew unavailability was observed to be the best surrogate objective function for reserve crew schedules that perform well in simulation. A list of extensions that can be made to the model is then given, followed by a conclusion that summarises the findings and important results obtained. Graphs / Networks Room: A26 (16:00 - 17:30) Chair: Michael Clark 1. The design of transportation networks: a multi objective model combining equity, efficiency and efficacy Maria Barbati1,в€— 1 в€— University of Naples Federico II; [email protected] A districting problem consists in subdividing a given region into a certain number of sub-regions (districts) on the basis of an objective function to optimize. This kind of problem can occur in different fields of application when a service (public or private) has to be provided in a region. The decision about the number of districts and the allocation of the potential users to the district affects the management of the service in terms of costs and accessibility of the service. In order to solve these problems, various models have been proposed with different characteristics in dependence of the service type, the objective and the constraints to be considered. After a general description of the models able to represent districting problems, we propose a mathematical formulations to define appropriate districts when a public service has to be organized and managed on a territory. An application of the model to the case of a school districting problems is described and the results of a real case are analyzed and discussed. 3. Modelling the uncertainty of data and the robust shortest path Michael Clark1,в€— and Andrew J. Parkes1 1 University of Nottingham; в€— [email protected] Most optimisation problems rely on perfect information in order for the algorithms to perform well. Often in real world situations this information is not available. Modifying an algorithm to handle such situations can lead to complications and in many cases is not possible. Changing a model to handle uncertain data increases the complexity of the problem. As a result of this measuring the quality of the solution is no longer a trivial process leading to a need for new approaches. Here we will describe different ways to model uncertainty and discuss their application to the robust shortest path problem. We will discuss different ways to calculate the cost of robustness and show a simple algorithm, which is based on the A* Search Heuristic. We will explain how graphs are generated, allowing different characteristics to be modelled. We will show the experiments run on the generated graphs and discuss the results. 1 University of Naples Federico II - Department of Engineering Management (DIEG); в€— [email protected] 34 SCOR 2012 Abstracts Sunday Multicriteria Decision Analysis II Room: A08 (10:00 - 11:00) Chair: Martin Takac 1. A non-identical parallel machines scheduling problem with multi-objective minimization Jean Respen1,в€— , Nicolas Zufferey1 and Edoardo Amaldi2 1 в€— HEC, University of Geneva; [email protected] Politecnico di Milano; Multi-objective production problems are becoming nowadays a regular faced issues for decision-makers who need to take the more accurate decision at the right moment. As exact methods are unable to tackle this kind of problems in a fair amount of time, researchers started to develop new and quick methods, called metaheuristics, which are able to find near-optimal solutions in reasonable amount of time. In this context, we propose a multi-objective scheduling problem based on non-identical parallel-machines. Makespan, setup costs and times, as well as smoothing issues are considered, and eligibility constraints are fulfilled. To tackle this complex problem, we propose different metaheuristics, such as tabu search and adaptive memory techniques, as well as an exact method (for comparison purposes on the small instances). We show that our algorithms are fast, efficient, and robust, even for big instances where exact methods cannot be considered, due to exponential computation times. Current results for the considered problems are presented and future works conclude the presentation. Hyper-heuristics have drawn increasing attention from the research community in recent years, although their roots can be traced back to the 1960вЂ™s. They perform a search over the space of heuristics rather than searching over the solution space directly. Research attention has focussed on two types of hyper-heuristics: selection and generation. A selection hyper-heuristic manages a set of low level heuristics and aims to choose the best heuristic at any given time using historic performance to make this decision, along with the need to diversify the search at certain times. In this study, we propose a choice function based hyper-heuristic for multi-objective optimization that controls and combines the strengths of three well-known multi-objective evolutionary algorithms (NSGAII, SPEA2, and MOGA), which are utilised as the low level heuristics. A choice function acts as the high level strategy, which adaptively ranks the performance of three lowlevel heuristics, deciding which one to call at each decision point. вЂњAll MovesвЂќ is employed as an acceptance strategy, meaning that we accept the output of each low level heuristic whether it improves the quality of the solution or not. Four performance metrics (Algorithm effort (AE), Ratio of non-dominated individuals (RNI), Size of space covered (SSC) and Uniform distribution of a non-dominated population (UD)) act as an online learning mechanism to provide knowledge of the problem domain to the high level strategy. The experimental results demonstrate the effectiveness of this hyper-heuristic approach when tested on the Walking Fish Group test suite, a common benchmark for multi-objective optimization. 2. A hybrid encoding scheme for grouping problems Anas Abdalla Osman Elhag1,в€— and Ender Г–zcan1 1 2. Decision analysis for cost effective maintenance of trunk roads Ena Orugbo1,в€— and Alkali Babakalli1 1 Glasgow Caledonian University; в€— [email protected] This paper investigates the dynamics of road network category1 defect accumulation and failure process. Category1 defects are failings that significantly accelerate structural deterioration and present hazards to road users. The study establishes appropriate insight into hazards related failures and interrelationship between trunk road sub-assets. Higher incidence of defects due to up-comings such as growing traffic has led to increased maintenance works. This works impede efforts to meet ever increasing demands for safe and reliable journeys. Reliability Centred Maintenance (RCM) and a Delphi expert survey are conducted on XYZ trunk road network. A Multiple Criteria Decision Analysis (MCDA) is to be conducted using Analytical Hierarchical Process (AHP) to set the pace for the development of a Road Defect Maintenance Model (RDMM). The results from the RCM, downtime and sub-asset history failure data analysis are presented. Further investigation and modelling that could support cost-effective trunk road maintenance decisions is on-going. Optimisation V Room: A24 (10:00 - 11:00) Grouping problems represent a family of combinatorial optimization problems where the task is to partition a single set of objects into a collection of mutually disjoint subsets such that each object is in exactly one subset. Linear Linkage Encoding and the Genetic Grouping Algorithm Representation are two different encoding schemes that have been used to solve the grouping problems. In this study, a hybrid encoding scheme that combines the benefits from both representations is investigated. Additionally, crossover and mutation operators based on the hybrid encoding scheme are described. These operators can be used in any appropriate algorithmic framework for solving grouping problems. The initial results will be provided at the conference using a selection hyper-heuristic framework for graph colouring as a case study. Scheduling / Timetabling II Room: A25 (10:00 - 11:00) Marcin Siepak1,в€— Chair: Alessia Violin 1. A choice function based hyper-heuristic for multi-objective optimization Mashael Maashi1,в€— , Graham Kendall1 and Ender Г–zcan1 University of Nottingham; в€— [email protected] SCOR 2012 Chair: Urszula Neuman 1. An exact algorithm for the uncertain version of parallel and identical machines scheduling problem with interval processing times and total completion time criterion 1 в€— 1 University of Nottingham; в€— [email protected] Wroclaw University of Technology; [email protected] An uncertain version of parallel and identical machines scheduling problem with the total completion time criterion is considered. It is assumed that the execution times of tasks are not known a priori but they belong to the intervals of known bounds. Such a way of uncertainty description is useful in the cases where no any historical data is available regarding the imprecise parameters, which would be required in order to obtain the probability distribution and apply the 35 Abstracts Sunday stochastic approach and also when there is lack of experts opinions which would be a source of other representations of uncertain execution times, e.g. in the form of membership function for the fuzzy approach. The absolute regret based approach for coping with such an uncertainty is applied. This problem is known to be NP-hard and a branch and bound algorithm (B&B) for finding the exact solution is developed. The results of computational experiments show that for the tested instances of the uncertain problem вЂ“ B&B works significantly faster that the exact procedure based on a simple enumeration. The algorithm proposed has application for further research of quality evaluation for planned to develop heuristic and approximate solution approaches for the considered problem - in order to check how far from the optimality are solutions generated by them. It also allows to obtain the exact solution for small instances of the uncertain problem faster than an algorithm based on a simple enumeration. 2. Optimizing real-world workforce scheduling problems Nico KyngГ¤s1,в€— 1 в€— Satakunta University of Applied Sciences; [email protected] The process of constructing optimized work timetables for the personnel is an extremely demanding task, hence the use of decision support systems for workforce scheduling has become increasingly important for both the public sector and private companies. Good rosters have many benefits for an organization, such as lower costs, more effective utilization of resources and fairer workloads. The workforce scheduling process includes four phases: 1) shift generation is the process of determining the shift structure, 2) in preference scheduling employeesвЂ™ wishes are fulfilled as well as possible, 3) days-off scheduling deals with the assignment of rest days between working days, 4) staff rostering deals with the assignment of employees to shifts. The paper presents a process and a method for optimizing real-world workforce scheduling instances. My current research deals with shift generation and large-scale staff rostering, hence those topics will be given emphasis in the presentation. A population-based local search heuristic called PEAST is used to solve the workforce optimization phases. The generated software is in real-world use. Tarifa Almulhim1,в€— and Ludmil Mikhailov1 в€— Manchester Business School; [email protected] A non-linear extension of the fuzzy preference programming (FPP) method for deriving group priorities in the Fuzzy Analytical Network Process (FANP) is proposed. The proposed method considers the different important weights for multiple decision makers (DMs). Additionally, it allows for representation DMs preferences as fuzzy numbers rather than exact numerical assessments in order to tackle the uncertainty and imprecision in human thinking. The proposed method also transfers the group prioritization problem in the FANP into a nonlinear program. Unlike the known fuzzy prioritization techniques, the efficacy of the proposed method is demonstrated for deriving crisp weights from incomplete and inconsistency fuzzy set of comparison judgements. Moreover, it doesnвЂ™t require additional aggregation producers and provides a consistency index for measuring the inconsistency of the DMsвЂ™ uncertainty judgements. Numerical examples are 36 Timo P. Kunz1,в€— 1 Lancaster University; в€— [email protected] In recent years, Revenue Management has found its way into retail industry practice, where previously high counts of sales outlets and products, and the resulting masses of data had limited the proliferation of the revenue management idea. However, price optimization theory and practice are still largely disconnected. While the relevant contributions in the area of forecasting and demand modelling are usually driven by empirical data but rarely address the pricing problem, the price optimization and revenue management literature tends to focus on the theoretical optimization problem paying little attention to the empirical relevance and applicability of the underlying demand model. Our research aims to fill this gap by taking an integrated look and highlighting the interplay of the individual components of the optimization system, namely the interaction between optimization and demand models along with the empirical data that is used for the estimation and the calibration of the later. The findings up to this point suggest that the most pressing issue from an operational perspective are to be found in the applicability and empirical validation of the prevalent market share modelling approach via attraction/choice models. Further the work aims to highlight the relevance of the categoryвЂ™s competitive structure for the demand modelling and the optimization problem alike. Simulation / System Dynamics Room: A08 (13:30 - 15:00) Chair: Magdalena Gajdosz 1. The transition to an energy sufficient economy: a system dynamics model for energy policy evaluation in Nigeria 1 Chair: Stefan Ravizza 1. Deriving priorities from fuzzy group comparison judgements in the fuzzy analytical network process (FANP) 1 2. Modelling retail sales for retail price optimization Timothy Mbasuen1,в€— and Richard C. Darton1 Decision Support Room: A26 (10:00 - 11:00) illustrated the implement of the proposed method and compared to the existing fuzzy prioritization method. University of Oxford; в€— [email protected] Nigeria is an energy-rich developing country with a huge energy resource base. The country is currently the largest reserves holder and largest producer of oil and gas in the African continent. However, despite this, only 40% of the countryвЂ™s 158 million people have access to modern energy services. About 80% of its rural dwellers depend almost wholly on traditional biomass for their energy needs. Several attempts by the government; to improve this situation have failed to produce the desired results. This paper presents an overview of ongoing research being undertaken to examine energy policies in Nigeria, with the aim of identifying and quantifying the barriers of sustainable energy development in that country. System dynamics modelling is shown to be a useful tool to map the interrelations between critical energy variables with other sectors of the economy, and for understanding the energy use dynamics within the economy. It is found in our preliminary analysis that the critical factors are lack of energy sector capacity utilisation, inadequate energy financing/investment, lack of trained and suitably qualified manpower, as well as inconsistencies and policy reversals. These remain the key challenges hampering NigeriaвЂ™s smooth transition from energy poverty to an energy sufficient economy. SCOR 2012 Abstracts Sunday 2. On the Peter principle: an agent based investigation into the consequential effects of social networks and behavioural factors Angelico Fetta1,в€— , Paul Harper1 , Vincent Knight1 , Israel Vieira1 and Janet Williams1 1 Cardiff University; в€— [email protected] The Peter Principle is a theory that provides a paradoxical explanation for job incompetence in a hierarchical organisation. It argues that should staff be competent at a given level, their competence may not be implicit at higher levels due to the differences in the skill set required. Furthering the work of a recent investigation into the Peter Principle utilising Agent Based Simulation, this paper explores external factors upon varying promotion strategies to assess efficiency. Through additional elements of social networks, behavioural dynamics and social capital, a more representative view of workplace interaction is presented. Results from the simulation found that although the Peter Principle affects efficiency, it may not be to the levels previously suggested and could be influenced by social network topology. Furthermore promotion on merit provided the most favourable maximum and minimum efficiency margins, given the absence of clear evidence pertaining to the existence of the Peter Principle. 3. Empirical bayes methods for discrete event simulation Shona Blair1,в€— , John Quigley1 and Tim Bedford1 1 в€— University of Strathclyde; [email protected] Discrete event simulation (DES) is widely utilized in OR applications for the design, analysis and improvement of complex, dynamic and stochastic real-world systems. One of the key advantages of discrete event simulation is its ability to incorporate a вЂњrealisticвЂќ level of system complexity into the analysis process, as opposed to the more rigid assumptions of alternative modelling techniques. This, however, frequently results in simulation models which are large-scale, structurally complex and computationally expensive to run. As such, careful statistical analysis of experimental results is necessary to ensure efficient use of DES models. Empirical Bayes (EB) procedures offer a structured and theoretically sound framework for the pooling of data obtained across a set of populations to support inference concerning the parameters of an individual population. This often enables more efficient inference in situations which feature a repeated structure, providing that sufficient вЂњsimilarityвЂќ exists between component elements. It seems intuitively reasonable that such an approach may be of benefit in DES model experimentation, owing to the underlying similarity between model configurations. In light of the computational expense involved in executing simulation models, such increased efficiency in estimation would likely prove highly advantageous in practice. Despite this potential, EB has so far been neglected in the simulation literature. In this talk, the results of a pilot study into the use of EB procedures in the estimation of DES performance measures will be presented. In addition, the practical significance of the results, and directions for further research will also be discussed. Chair: Pablo Gonzalez Brevis 1. The k-separator problem Mohamed Sidi Mohamed Ahmed1,в€— , Walid Ben-Ameur1 and Jose Neto1 SCOR 2012 Telecom Sudparis; [email protected] Let G = (V;E;w) be a vertex-weighted undirected graph and k be a positive number. We want to compute a minimum-weight subset of vertices S whose removal leads to a graph where the size of each connected component is less than or equal to k. Let us call such a set a k-separator. If k = 1 we get the classical vertex cover problem. The case k = 2 is equivalent to compute the dissociation number of a graph (in the case of unit weights). This problem is NP-hard even if the graph is bipartite. The k-separator problem has many applications. If vertex weights are equal to 1, the size of a minimum k-separator can be used to evaluate the robustness of a graph. Intuitively, a graph for which the size of the minimum k-separator is large is more robust. Unlike the classical robustness measure given by the connectivity, the new one seems to avoid to underestimate robustness when there are only some local weaknesses in the graph. The minimum k-separator problem has also some applications in the context of networks. A classical problem consists in partitioning a graph into different subgraphs with respect to different criteria. For example, in the context of social networks, many approaches are proposed to detect communities. By solving a minimum k-separator problem, we get different connected components that may represent communities. The k-separator vertices represent persons making connections between communities. в€— 2. A multi-dimensional multi-commodity covering problem with application in logistics Alexander Richter1,в€— , Jannik Matuschke1 and Felix KГ¶nig1 TU Berlin; в€— [email protected] In this talk, we study a multi-commodity multi-dimensional covering problem which we encountered as a subproblem in optimising large scale transportation networks in logistics. The problem asks for a selection of containers for transporting a given set of commodities, each commodity having different extensions of properties such as weight or volume. Each container is specified by a fixed charge and capacities in the relevant properties and can be selected multiple times. The task is now to find a cost minimal collection of containers and a feasible assignment of the demand to all selected containers. From theoretical point of view, by exploring similarities to the well known set cover problem, we derive NP-hardness and see that the non-approximability result known for set cover also carries over to our problem. For practical applications we need very fast heuristics to be integrated into a meta-heuristic framework thatвЂ”depending on the contextвЂ” either provide feasible near optimal solutions or only estimate cost value of an optimal solution. Thus, in a second part we develop and analyse a flexible family of greedy algorithms that meet these challenges. In order to find best-performing configurations for different requirements of the meta-heuristic framework, we provide an extensive computational study on random and real world instance sets obtained from our project partner 4flow. We outline a trade-off between running times and solution quality and conclude that the proposed methods achieve the accuracy and efficiency necessary for serving as a key ingredient in more complex meta-heuristics. 1 Scheduling / Timetabling III Optimisation VI Room: A24 (13:30 - 15:00) 1 Room: A25 (13:30 - 15:00) Chair: Urszula Neuman 1. Flexible mobile workforce scheduling and routing Jose Arturo Castillo Salazar1,в€— and Dario Landa-Silva1 37 Abstracts University of Nottingham; в€— [email protected] In times where employees need to be more flexible and mobile regarding the types of jobs they perform, a range of problems arise. Such problems, like home health care and technicians scheduling, require employees travelling using different transportation modalities. Employees move across many diverse locations to do work related tasks. Tasks are activities which have specific starting time and duration. Moreover, employees necessitate appropriate skills related to their performing tasks. Skills vary for every employee, resulting in a widely diverse workforce. Some tasks need to be synchronised and appropriately sequenced. The motivation of this study is to gather the most common characteristics of such problems in order to develop an algorithm to solve them. In the context of this study, we refer to these problems as flexible mobile workforce scheduling and routing (FMWSR). The FMWSR problem is a hybrid one, combining concepts from vehicle routing with time windows and employee scheduling. The outcome is a set of typical features from the literature: time windows, transportation modality, start and end locations, skills and qualifications, service time, connected activities, teaming and clusterisation, the last two being optional. Solving FMWSR problems has many objectives such as reducing employeesвЂ™ travel time, guaranteeing tasks are performed by qualified personnel and reducing costs. Devon Barrow1,в€— and Sven Crone1 1 1 Lancaster University; в€— [email protected] Since its origins in the mid 1990s, boosting has been successfully applied in over 2500 studies emerging as one of the best ensemble algorithms in classification and regression. In contrast a recent survey noted only 15 papers applying boosting to forecasting time series data. None of these investigate the interaction between the algorithm meta-parameters and their impact on forecast performance. To close this gap we describe based on original AdaBoost, a generic algorithm whose components correspond to different meta-parameter choices. We evaluate the influence of combination method, loss function, stopping criteria and a new meta-parameter based on the choice of loss update model. Within this framework well known AdaBoost.R2 and AdaBoost.RT are easily identified as a choice of these four factors. Boosting is applied to Multilayer Perceptron (MLP) networks to forecast the NN3 competition real world dataset of 111 time series containing long and short, seasonal and non-seasonal time series. A multifactorial analysis of variance (MANOVA) on forecast errors provides empirical evidence that different meta-parameter choices have a significant impact on forecast accuracy, with certain parameter choices proving superior to standard boosting approaches adopted in classification and regression. 2. A case study of investigating a highly constrained search space 2. Long-term reserve warranty forecasting with neural network models Lisa Taylor1,в€— , Jonathan Thompson1 and Rhyd Lewis1 Cardiff University; в€— [email protected] In this research we have focussed on a post enrolment-based problem (International Timetabling Competition 2007), looking particularly at maximising the connectivity of the search space. When dealing with timetabling problems that are subject to both hard and soft constraints, a common strategy is to make use of a two-stage optimisation process. Stage one consists of satisfying the hard constraints whilst stage two is to minimise the soft constraint violations. A highly constrained problem can mean that a search space is disconnected; that is, feasible regions are separated by an infeasible region under certain neighbourhood operators. Our research focuses on searching highly constrained solution spaces and means of navigating between feasible regions. In stage one, we looked at two strategies. The first strategy schedules all events using saturation degree. The events were then re-arranged using neighbourhood operators. The second strategy allows unplaced events and inserts them using a type of maximum matching algorithm. The second strategy works much better because the first strategy unnecessarily constrains the problem. Stage two entails optimising the feasible solution in terms of a soft constraint penalty. We found a strong correlation between the number of moves that can be performed whilst maintaining feasibility and the improvement made to the soft constraint penalty. We can use this information to achieve further improvements. For instance, adding more neighbourhood operators to increase the number of moves that maintain feasibility; and temporarily removing events from the timetable making more spaces available for the scheduled events to move to. Shuang Xia1,в€— and Shaomin Wu1 1 Neural Networks / Machine Learning Room: A26 (13:30 - 15:00) Chair: Martin Takac 1. A meta-parameter analysis of boosting for time series forecasting 38 1 Cranfield University; в€— [email protected] Forecasting future warranty reserves is vitally important for warranty suppliers. Many techniques in this area exist in the literature. However, little work has been done on long-term warranty reserve forecasting, while it is an important issue in making fiscal plan. This paper develops two neural network models to forecast warranty reserves. It compares the two techniques based on both artificially generated data and data collected from an electronics product manufacturer. 3. Inventory optimization under process flexibility assumption using approximate dynamic programming approaches Mustafa Cimen1,в€— , Kevin Glazebrook1 and Christopher Kirkbride1 1 Lancaster University; в€— [email protected] Classical inventory problem requires optimizing two decisions: when and how much to produce. Even though process flexibility (being able to produce multiple products in each factory) provides the ability to react rapidly to changes in or results of stochastic environment, inventory decisions are even more complex under this assumption, as decision maker also needs to give decisions of how much to produce each product in each factory, which depends on each other. In this study, we use Machine Learning (known also as Approximate Dynamic Programming (ADP) in OR literature) approaches to cope with this complex system. We define a small-sized stochastic inventory problem under capacity constraint and process flexibility assumptions, and solve the decision problem by several look-up table ADP approaches and step-size parameter selections. Two main goals of these computations are (i) showing how capable ADP is to cope with this kind of problems, and (ii) making a comparison of performances of various ADP algorithms. SCOR 2012 Index of Authors Index of Authors Abd Rahmin, Nor Aliza, 31 Al Hinai, Ahmed, 28 Almulhim, Tarifa, 36 Armstrong, Stanislava, 23 AscГі, Amadeo, 34 Baeklund, Jonas, 24 Barbati, Maria, 34 Barrow, Devon, 38 Bayliss, Christopher, 34 Blair, Shona, 37 Booker, Carolyn, 23 Castillo Salazar, Jose Arturo, 37 Chen, Hanyi, 26 Cimen, Mustafa, 38 Clark, Michael, 34 Cookson, Emily, 33 Crespo Del Granado, Pedro, 33 D. Nasiri, Saeideh, 27 Djeumou Fomeni, Franklin, 26 Djordjevic, Lena, 31 Djordjevic, Milan, 26 Drake, John, 29 Dursun, Pinar, 30 Peano, Andrea, 24 Piccolo, Carmela, 34 Rauscher, Sandra, 30 Reddy, Brian, 25 Respen, Jean, 35 Richter, Alexander, 37 Rostami Tabar, Bahman, 28 Rowse, Elizabeth, 32 Schulze, Tim, 26 Schurr, Jochen, 26 Shone, Rob, 23 Siepak, Marcin, 35 Silvera, Yolanda, 27 Smith, Leanne, 32 Soulby, Matthew, 27 Swarat, Elmar, 23 TakГЎЛ‡c, Martin, 31 Tar, PГ©ter, 30 Taylor, Lisa, 38 Thevenin, Simon, 31 Umofia, Anietie, 29 Velandia-Brinez, Cesar, 24 Elhag, Anas Abdalla Osman, 35 Williams, Julie, 28 Fetta, Angelico, 37 Xia, Shuang, 38 Gajdosz, Magdalena, 29 Geranios, Michail, 30 Goetzmann, Kai-Simon, 25 GonzГЎlez-Brevis, Pablo, 24 Guajardo, Mario, 33 Holborn, Penny, 27 Huynh, Nha-Nghi, 28 Kent, Edward, 31 Kheiri, Ahmed, 29 Komenda, Izabela, 32 Kunz, Timo P., 36 KyngГ¤s, Nico, 36 Lai, Michela, 27 Lutter, Pascal, 32 Maashi, Mashael, 35 Mari, Renato, 25 MarinoviВґc, Minja, 23 Mbasuen, Timothy, 36 Mohamed Ahmed, Mohamed Sidi, 37 Morales Enciso, Sergio, 33 Neuman, Urszula, 32 Ntio, Despoina, 30 Orugbo, Ena, 35 SCOR 2012 39