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:: Volume 1, Issue 3 (11-2014) ::
IJSOM 2014, 1(3): 279-296 Back to browse issues page
An Efficient Genetic Algorithm to Solve the Intermodal Terminal Location problem
Mustapha Oudani * 1, Ahmed El Hilali Alaoui 2, Jaouad Boukachour 3
1- Laboratoire de Mathématiques Appliquées du Havre ,
2- Modeling and Scientific Computing Laboratory
3- Laboratoire de Mathématiques Appliquées du Havre
Abstract:   (3277 Views)
The exponential growth of the flow of goods and passengers, fragility of certain products and the need for the optimization of transport costs impose on carriers to use more and more multimodal transport. In addition, the need for intermodal transport policy has been strongly driven by environmental concerns and to benefit from the combination of different modes of transport to cope with the increased economic competition. This research is mainly concerned with the Intermodal Terminal Location Problem introduced recently in scientific literature which consists to determine a set of potential sites to open and how to route requests to a set of customers through the network while minimizing the total cost of transportation. We begin by presenting a description of the problem. Then, we present a mathematical formulation of the problem and discuss the sense of its constraints. The objective function to minimize is the sum of road costs and railroad combined transportation costs. As the Intermodal Terminal Location Problemproblem is NP-hard, we propose an efficient real coded genetic algorithm for solving the problem. Our solutions are compared to CPLEX and also to the heuristics reported in the literature. Numerical results show that our approach outperforms the other approaches.
Keywords: Intermodal transportation, Terminal, Genetic Algorithm, Meta-heuristic, Rail-truck, Optimization
Type of Study: مقاله پژوهشی |
ePublished: 2017/09/28
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Oudani M, El Hilali Alaoui A, Boukachour J. An Efficient Genetic Algorithm to Solve the Intermodal Terminal Location problem. IJSOM. 2014; 1 (3) :279-296

Volume 1, Issue 3 (11-2014) Back to browse issues page
International Journal of Supply and Operations Management International Journal of Supply and Operations Management
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