Optimization of multimodal transportation problems
Identifieur interne : 000008 ( Main/Exploration ); précédent : 000007; suivant : 000009Optimization of multimodal transportation problems
Auteurs : Mustapha Oudani [France]Source :
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Abstract
This thesis is a contribution to research on the optimization of multimodal transport problems. The main key concepts of multimodality in the intermodal transportation networks and the state of the art of scientific works in the field are presented. The intermodal terminal location problem is then studied. We propose a genetic algorithm with mixed encoding for solving this problem and we compare our results with those of literature. A set of problems in the framework of our work on the project DCAS (Direct Cargo Axe Seine), carried by the Grand Port Maritime du Havre, are described and modeled by mathematical programming tools. Thus, we studied the problem of the transfer of rail shuttles which is to optimize the transfer of a set of containers between maritime terminals and a multimodal terminal. We then modeled the scheduling problem of freight trains for placement on rail tracks. These problems are solved by using combined optimization simulation approaches. A first application is based on a genetic algorithm coupled with the multi agent’s simulation. A second is to optimize a rail-rail transshipment of containers using an ant colony algorithm embedded in the simulation model and an agent’s collaboration strategy to minimize waiting times and increase cranes productivity.
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The main key concepts of multimodality in the intermodal transportation networks and the state of the art of scientific works in the field are presented. The intermodal terminal location problem is then studied. We propose a genetic algorithm with mixed encoding for solving this problem and we compare our results with those of literature. A set of problems in the framework of our work on the project DCAS (Direct Cargo Axe Seine), carried by the Grand Port Maritime du Havre, are described and modeled by mathematical programming tools. Thus, we studied the problem of the transfer of rail shuttles which is to optimize the transfer of a set of containers between maritime terminals and a multimodal terminal. We then modeled the scheduling problem of freight trains for placement on rail tracks. These problems are solved by using combined optimization simulation approaches. A first application is based on a genetic algorithm coupled with the multi agent’s simulation. A second is to optimize a rail-rail transshipment of containers using an ant colony algorithm embedded in the simulation model and an agent’s collaboration strategy to minimize waiting times and increase cranes productivity.</div></front></TEI><affiliations><list><country><li>France</li></country><region><li>Haute-Normandie</li><li>Région Normandie</li></region><settlement><li>Le Havre</li></settlement><orgName><li>Université du Havre</li></orgName></list><tree><country name="France"><region name="Région Normandie"><name sortKey="Oudani, Mustapha" sort="Oudani, Mustapha" uniqKey="Oudani M" first="Mustapha" last="Oudani">Mustapha Oudani</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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