A multi-space sampling heuristic for the vehicle routing problem with stochastic demands
Résumé
The vehicle routing problem with stochastic demands consists in designing transportation routes of minimal expected cost to satisfy a set of customers with random demands of known probability distribution. This paper proposes a novel heuristic approach that uses randomized heuristics for the traveling salesman problem, a tour partitioning procedure, and a set-partitioning formulation to sample the solution space and find high-quality solutions for the problem. Computational experiments on benchmark instances from the literature show that the proposed approach outperforms the state-of-the-art algorithm for the problem in terms of both accuracy and efficiency.
Domaines
Recherche opérationnelle [math.OC]
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Mendoza_and_Villegas_2011_-_A_multi-space_heuristic_for_the_VRPSD_working_paper_.pdf (543.14 Ko)
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