1. Hjemmeside www.dtu.dk/Nyheder/Kalender 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 (abjo@dtu.dk)

2. 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 (abjo@dtu.dk)

3. 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 diffcult 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.