PhD Defence
Christian Edinger Munk Plum:
Optimization of Container Line
Networks with Flexible Demands
Monday, June 17, 2013, 13:00
Technical University of Denmark
Building 101, S10
Supervisor:
Professor David Pisinger, DTU Management Engineering,
Management Science
Co-supervisor:
Optimization Manager, PhD Mikkel Mühldorff Sigurd, Maersk
Assessment Committee:
Associate Professor Stefan Røpke (Chairman),
DTU Management Engineering, Management Science
Professor Kjetil Fagerholt, Norwegian University of Science and Technology,
Department of Industrial Economics and Technology Management
Associate Professor Qiang Meng, National University of Singapore,
Department of Civil and Environmental Engineering
Moderator:
PostDoc Richard Lusby,
DTU Management Engineering, Management Science
After the defence, there will be a reception at Management Science
bld. 426 B, room 047. A copy of the thesis is available in the reception in
bld. 424. Contact: Division Secretary Anja Johansen ([email protected])
Hjemmeside
www.dtu.dk/Nyheder/Kalender
Ph.D.-forsvar
Christian Edinger Munk Plum:
Optimization of Container Line
Networks with Flexible Demands
Mandag d. 17. juni, 2013, 13:00
Danmarks Tekniske Universitet
Bygning 101, S10
Vejleder:
Professor David Pisinger,
DTU Management Engineering, Management Science
Medvejleder:
Optimization Manager, PhD Mikkel Mühldorff Sigurd, Maersk
Bedømmelsesudvalg:
Professor Stefan Røpke (formand),
DTU Management Engineering, Management Science
Professor Kjetil Fagerholt, Norges Teknisk-Naturvidenskabelige Universitet,
Institut for Industriel Økonomi og Teknologiledelse.
Lektor Qiang Meng, National University of Singapore,
Department of Civil and Environmental Engineering
Ordstyrer:
PostDoc Richard Lusby
DTU Management Engineering, Management Science
Efter forsvaret er der reception hos Management Science i byg. 426 B, rum 047.
Kopi af afhandlingen forefindes i Receptionen i byg. 424.
Kontakt: Afdelingssekretær Anja Johansen
([email protected])
Hjemmeside
www.dtu.dk/Nyheder/Kalender
Christian Edinger Munk Plum:
Optimization of Container Line Networks
with Flexible Demands
Liner shipping is at the core of the world's supply chains, with an estimated 36 % of the
value of global merchandize trade being shipped in containers. The containers, carried
on thousands of container vessels in intricate networks operated by global liner
shipping carriers, constitute a very important part of the world economy.
Container carriers operate in a highly competitive market, where the assets must be
deployed in the best way possible to create a healthy business. To better manage the
assets invested in container shipping and to control the use of fossils fuels used by the
liner shipping industry, optimization methods for liner shipping is studied in this thesis.
From a mathematical point of view these problems are among the very hardest, in the
class of NP-hard problems. And when considering network design problems, these are
among the most diff cult of NP-hard problems, which rarely can be solved to optimality
for medium or large instances. A thorough description of the domain of liner shipping is
given, explaining the industry in the words of an operations researcher. At the same
time a set of benchmark instances LINER-LIB 2012 is introduced.
Three different approaches for liner shipping network design are presented. The
first presents a model that allows for the creation of services (loops of vessels,
following the same route) connecting to form a liner shipping network.
A second approach to liner shipping network design, models how demand can flow on
services, as opposed to flowing directly between ports. This allows for the creation of
more complicated networks than previously seen. Lastly a model focusing on the
design of a single service is considered.
The two last chapters considers operational decision problems met in liner shipping.
Bunker fuel is a huge expense for a liner shipping company, and at current market
rates it constitutes up to 30 % of a networks operational cost, equaling in billions of
dollars for large container carriers. A model handling this is developed which allows a
global liner carrier to efficiently plan bunker purchases for their vessels, using a large
number of bunker contracts to lower costs.
Container vessels operate on tight schedules to meet the customers transit time
requirements and reach their port berth slots. Often disruptions occur to the schedules
due to adverse weather, mechanical failures and port delays. A mixed integer
programming model is developed, which can suggest an optimal mitigation for a given
disruption. The model is run on four real cases, finding optimal solutions in less than 5
seconds. The cases show up to 58 % savings in recovery costs compared to manually
realized recovery costs.
Hjemmeside
www.dtu.dk/Nyheder/Kalender