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Detailed schedule
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Show all the abstracts
Show all the abstracts
Thursday 11:00:00 Timetabling in education and sport Room 126 - Chair: G. Vanden Berghe
Thursday 11:00:00 Transportation management Room 130 - Chair: F. Semet
- Incorporating logistics decisions in activity-based freight modeling
Tabitha Maes (Hasselt University) Co-authors: Katrien Ramaekers, An Caris, Tom Bellemans, Gerrit Janssens
- A GRASP metaheuristic for allocating resources to improve the accessibility in a road network after a natural disaster
Pablo Andres Maya Duque (University of Antwerp ) Co-authors: K. Sorensen, P. Goos
- Vehicle loading optimization with stochastic supply
Thierry Pironet (Université de Liège) Co-authors: Amand, Arda, Crama, Kronus, Pironet
- Location and market area of rail-road terminals
Sabine Limbourg (HEC-ULg) Co-authors: B. Jourquin Abstract: The European transport policy has focused on sustainable transport solutions. One of its objectives for freight transport is to restore the balance between modes and to develop intermodality. Among the various types of intermodal transports, this research is concerned with rail-road container terminals embedded in a hub-and–spoke network. These terminals will further be referred to as hubs.
Hub-and-spoke networks have been implemented in a number of transportation systems when it is favourable to consolidate and disseminate flows at certain locations called hubs. The efficiency of such a network depends on the location of the hubs. The problem is to find the optimal hub locations and to allocate the remaining nodes to these hubs. This problem is known as the p-hub median problem (p-HMP) where p is the number of hubs to locate.
This location-allocation problem is proved to be NP-hard. The time needed to solve it increases as the number of nodes exponent three. Thus, in order to model rail-road transport on the trans-European networks, a subset of nodes that can be considered as good potential locations is needed. We applied the p-HMP to a set of potential locations obtained by both spatial aggregation of demand nodes using hierarchical clustering methods and by a flow-based approach which takes the flows of commodities and their geographic spread into account. They showed that the latest method gives better results and that is why it is retained to determine a set of potential locations.
The set of potential locations is used as input for an iterative procedure. One of the main contributions of this research is to propose this iterative procedure based on both the p-HMP and the multi-modal assignment problem. Moreover, the objective function of our p-hub median formulation includes the costs for pre- and post-haulages by road, trans-shipment (according to the number of handled containers into account) and rail haulage. Furthermore, in the p-hub median problem, the total demand is assigned to the hubs. In this research however, the demand can be assigned over all the transportation modes, with the possibility (but not the obligation) of using the trans-shipment facilities.
Finally, we presents a methodology able to compare road and rail-road intermodal market areas that takes the network structures, the operation costs and the location of the rail-road terminals into account. This methodology is applied to the optimal configurations obtained by the resolution of the p-HMP and the p-hub centre problem (p-HCP) for the whole trans-European network. Indeed, p-HMP has an efficiency goal by minimizing the total transportation cost. The hub network design obtained by this method can sometimes lead to unsatisfactory results when worst-case origin-destination pairs are separated by a very large distance. Therefore, the p-HCM meets the equity objective by minimizing the maximum cost of a combined transport.
Thursday 11:00:00 Networks Room 138 - Chair: B. Fortz
Thursday 11:00:00 Nonconvex optimization 1 Room 035 - Chair: F. Bach
Thursday 14:00:00 Constraint programming models 1 Room 126 - Chair: Y. Deville
Thursday 14:00:00 Vehicle routing Room 130 - Chair: S. Limbourg
Thursday 14:00:00 Combinatorial optimization and IP applications Room 138 - Chair: Q. Louveaux
Thursday 14:00:00 Nonconvex Optimization 2 Room 035 - Chair: R. Sepulchre
Thursday 16:10:00 Constraint programming models 2 Room 126 - Chair: P. Schaus
Thursday 16:10:00 Performance modeling Room 130 - Chair: G. Janssens
Thursday 16:10:00 Scheduling Room 138 - Chair: K. Sorensen
Thursday 16:10:00 Planning under uncertainty Room 035 - Chair: R. Leus
Friday 09:00:00 Metaheuristics Room 126 - Chair: J. Teghem
Friday 09:25:00 Production and distribution (9:25) Room 130 - Chair: Y. Arda
Friday 09:00:00 Multiple criteria Room 138 - Chair: R. Bisdorff
Friday 09:25:00 Stochastic models (9:25) Room 035 - Chair: L. Esch
Friday 11:00:00 Constraint programming and Supply Chain Management Room 126 - Chair: Y. Deville
Friday 11:00:00 OR in health management Room 130 - Chair: P. De Causmaecker
Friday 11:00:00 Rankings and importance indices Room 138 - Chair: JL. Marichal
Friday 11:00:00 Queueing Room 035 - Chair: S. Wittevrongel
Friday 15:10:00 Optimization software Room 126 - Chair: E. Loute
Friday 15:10:00 Integrated operations planning Room 130 - Chair: B. Raa
Friday 15:10:00 Cycles in graphs Room 138 - Chair: F. Spieksma
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