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Communication Dans Un Congrès Année : 2016

Evolutionary Multi-Objective Optimization Approach for the Vehicle Routing Problem with Uncertain Travel Time

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Résumé

In this paper, we deal with the vehicle routing problem with uncertain travel cost. Uncertainty can be modeled by a set of scenarios where each scenario may represent the travel costs assigned to all visited arcs of the graph associated to the problem. Herein, a hybrid multi-objective evolutionary-based approach is proposed, where several local strategies are used for approximately solving the robust vehicle routing problem (namely RVRP). Unlike several existing methods that often aggregate multiple objectives into a compromise function, the goal of the proposed approach is to simultaneously optimize both the number of vehicles to use and the worst total travel cost needed. The proposed approach has been tested on benchmark instances extracted from the literature and its obtained results are compared to those reached by a standard solver and one of the most recent method available in the literature. Encouraging results have been obtained.
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Dates et versions

hal-03617906 , version 1 (23-03-2022)

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  • HAL Id : hal-03617906 , version 1

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Hiba Bederina, Mhand Hifi. Evolutionary Multi-Objective Optimization Approach for the Vehicle Routing Problem with Uncertain Travel Time. 2016 4TH INTERNATIONAL CONFERENCE ON CONTROL ENGINEERING & INFORMATION TECHNOLOGY (CEIT), Dec 2016, Hammamet, Tunisia. ⟨hal-03617906⟩

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