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A hybrid metaheuristic algorithm for the vehicle routing problem with stochastic demands

Abstract : This article deals with the Vehicle Routing Problem with Stochastic Demands. To solve this problem, a hybrid metaheuristic combining a Memetic Algorithm and Greedy Randomized Adaptive Search Procedure is designed. The developed approach is tested on a 40 instances benchmark. The results are validated by comparing them to state of the art metaheuristics, they show that our method outperforms these metaheuristics in terms of quality and efficiency. A new testbed of 39 instances with up to 385 customers is also proposed and tested. This paper is the first one to deal with closer to real life size problems.
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https://hal-utt.archives-ouvertes.fr/hal-02477121
Contributor : Daniel Gavrysiak <>
Submitted on : Thursday, February 13, 2020 - 10:56:18 AM
Last modification on : Wednesday, July 22, 2020 - 9:14:03 AM

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Andres Gutierrez, Laurence Dieulle, Nacima Labadie, Nubia Velasco. A hybrid metaheuristic algorithm for the vehicle routing problem with stochastic demands. Computers and Operations Research, Elsevier, 2018, 99, pp.135-147. ⟨10.1016/j.cor.2018.06.012⟩. ⟨hal-02477121⟩

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