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Multi-criterion Tabu Search to Solve the Dynamic Carpooling Based on the Choquet Integral Aggregation

Sondes Ben Cheikh and Slim Hammadi
École Centrale de Lille, LAGIS FRE CNRS 3303, BP 48, 59651 Villeneuve d'Ascq Cedex-France
Abstract—Carpooling consists in sharing one’s personal vehicles with one or several passengers in order to share the related costs but also reduce traffic and CO2 emissions. Today, there are several studies that revolve around dynamic carpooling. The problem is how to assign every new passenger’s request to one or more vehicles. This assignment must be done in real time. However, most of these studies still remain in embryonic stage regarding automation and real time aspects. In addition, there is another big handicap, due to the problem’s high complexity, concerning the way to make the process perform efficiently. Therefore, this study adopts a Multi-criterion Tabu search (MTS), which is an evolutionary method based on explicit memory systems and several searching strategies designed to avoid the entrapments by local solutions. Then, to obtain a rigorous and meaningful evaluation of our solution, we use an original aggregative approach based on Choquet Integral which take into account the interaction, the compensation and avoid redundancy between criteria. Finally, to assess the merits of our approach we present a simulation study based on travel demand data from metropolitan of Lille-France. The simulation results indicate that the use of metaheuristic optimization methods improve the performance of our dynamic carpooling system.

Index Terms—dynamic carpooling, tabu search, choquet integral

Cite: Sondes Ben Cheikh and Slim Hammadi, "Multi-criterion Tabu Search to Solve the Dynamic Carpooling Based on the Choquet Integral Aggregation," Journal of Traffic and Logistics Engineering, Vol. 2, No. 2, pp. 126-132, June 2014. doi: 10.12720/jtle.2.2.126-132
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