END332E
Operations Research II
Dr. Y. İlker TOPCU
www.ilkertopcu.net www.ilkertopcu.org www.ilkertopcu.info
facebook.com/yitopcu
twitter.com/yitopcu
instagram.com/yitopcu
Dr. Özgür KABAK
web.itu.edu.tr/kabak/
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Course Information
 Credits:
3+0
 ECTS Credits: 7
 Type:
Compulsory
 Language:
English
 Web site:
web.itu.edu.tr/topcuil/ya/END332E
ninova.itu.edu.tr
3
Course description
 Integer Programming
 Branch and Bound / Cutting Planes Algorithms
 Combinatorial Optimization
 Multi objective decision making (Goal Programming)
 Markov Chains
 Non-Linear Programming
 Interior point algorithms
 Dynamic Programming
4
Course objectives
1. To use different mathematical modeling techniques
utilizing Operations Research (OR) methodology
2. To learn various methods that are used for
quantitative decision making
3. To find optimal solutions to problems
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Course learning outcomes
Students who pass the course will gain
1. ability to formulate and solve Integer Programming
problems
2. insight in Combinatorial Optimization
3. insight in Multi Objective (Goal Programming) and Multi
Attribute Decision Making
4. ability to formulate and solve Non-Linear Programming
problems
5. ability to formulate and solve Dynamic Programming
problems
6
Relationship between the course and
Industrial Engineering curriculum
Level of Contribution
Program Outcomes
a
b
c
d
e
f
g
h
i
j
k
l
m
n
o
1
2
Apply mathematics, science, and engineering principles
3
X
Ability to design and conduct experiments and interpret data
Ability to design a system, component, or process to meet desired needs
X
Ability to function on multidisciplinary teams
X
Abiliy to identify, formulate, and solve engineering problems
X
Understanding of professional and ethical responsibility
X
Ability to communicate effectively
The broad education necessary to understand the impact of engineering
solutions in a global context
Recognition of the need for and an ability to engage in a life-time education
Knowledge of contemporary issues
Ability to use the techniques, skills, and modern engineering tools necessary for
engineering practice
Ability to apply his/her knowledge in business
Knowledge and skills of management
Understanding of the environment and responsibility for changes in
technological, economical and social issues
To have a high degree of self-confidence and initiative
1: Little, 2. Partial, 3. Full
X
X
X
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References
Text book
 Winston W.L. (2004) “Operations Research: Applications and
Algorithms”, Brooks/Cole – Thomson Learning
Web site of the course
 Up-to-date lecture notes and supplements
 Solutions to exams and homework
 Previous exam questions
Books
 “Operations Research”, "Practical Management Science",
"Introduction to Management Science“, "Quantitative Analysis for
Management”, "Optimization in Operations Research",
"Introduction to Mathematical Programming“
Web sites of other courses
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Assessment Criteria
 Final exam (40%), 2 Midterm exams (40%),
2 Assignments (20%)
 All exams will be “open book”
 If your final exam grade is less than 30 or if your
average grade is less than 40, you will receive a letter
grade FF
 If you do not complete the following requirements, you
will receive a letter grade VF:
 One of your midterm exam grades must be more
than 30
 One of your HW grades must be more than 50
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Exams
Midterm exam 1
 Topics covered in the first six weeks
 March 22, Wednesday, 6:00 pm
Midterm exam 2
 Topics covered after week seven
 May 15, Monday, 6:00 pm
Final exam
 All topics
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Assignments
HW1
 Integer Programming
 March 1 – March 15
HW2
 NLP, Interior Point algorithms, Dynamic Prog.
 April 26 – May 3
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Cheating and Plagiarism
 Do not!
 Studying together to understand the material is fine,
but the work you hand in is to be your own.
 No cheating will be tolerated: A letter grade of F will
be given!
 You can constitute a group of maximum three students
to submit assignments. You may submit a unique report
for your group (of course plagiarism among assignment
groups is strictly forbidden).
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Schedule
Feb. 6-8
Feb. 13-15
Feb. 20-22
Feb. 27-Mar. 1
Mar. 6-8
Mar. 13-15
Mar. 20 (Mon.)
Mar. 22 (Wed.)
Mar. 27-29
Apr. 3-5
Apr. 10-12
Apr. 17-19
Apr. 24-26
May 1
May 3
May 8-10
May 15 (Mon.)
May 15 (Mon.)
Integer Programming, Formulating IP Problems
Formulating IP Problems (cont.)
Solving IP Problems
Solving IP Problems (cont.); HW1
Goal Programming
Markov Chains
PROBLEM SOLVING
MIDTERM I (18:00)
SPRING BREAK
Interior Point Methods, Introduction to Non-Linear Prog.
Int. to NLP (cont.)
Deterministic Dynamic Programming
Deterministic Dynamic Programming (cont.); HW2
LABOR AND SOLIDARITY DAY
Probabilistic Dynamic Programming
Probabilistic Dynamic Programming (cont.)
PROBLEM SOLVING
MIDTERM II (18:00)
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Assoc. Prof. Dr. Özgür Kabak
Office address
Management Faculty A311, Maçka, Istanbul
Phone
(212) 293 1300 /2039 office
/2073 secretary
Web site
web.itu.edu.tr/kabak/
E-mail address
[email protected]
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
Assoc. Prof. at Industrial Engineering department of ITU (2015)

Post-doc studies at Belgium Nuclear Research Centre (SCK.CEN)
(2009-2010)
 A fuzzy multi attribute decision making approach for nuclear
safeguards information management

Ph.D. in ITU Industrial Engineering programme (2008)
 Modeling supply chain network using possibilistic linear
programming and an application

Research interests
 Operations Research (Mathematical programming)
 Supply chain management
 Fuzzy decision making
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Prof. Dr. Y. İlker Topcu
Office address
Management Faculty C301, Maçka, Istanbul
Phone
(212) 293 1300 /2069 office - (532) 355 5045 mobile
Web site
www.ilkertopcu.net, www.ilkertopcu.org, www.ilkertopcu.info,
www.facebook.com/yitopcu, twitter.com/yitopcu
E-mail address
[email protected]
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
Professor at Industrial Engineering department of ITU (2011)

Associate Professorship in Operations Research (2005)

Ph.D. in ITU Engineering Management programme (2000)
 Integrated decision aid model for multi-attribute problem
solving

Ph.D. research at Centre for Decision Research of Leeds
University Business School (1998-1999)

Research interests
 Decision Analysis, Multi Criteria Decision Making, Group
Decision Making
 Operations Research / Management Science
 Logistics Management, Ethics in OR, Business Ethics,
Transp’n, Energy, Bidding and Tender Systems, Scheduling
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