Target aiming Pareto search and its application to the vehicle routing problem with route balancing

Authors:
Nicolas Jozefowiez;Frédéric Semet;El-Ghazali Talbi
Affiliations:
Laboratoire d'Informatique Fondamentale de Lille, Université des Sciences et Technologies de Lille, Villeneuve d'Ascq, France;Laboratoire d'Automatique, de Mécanique et d'Informatique industrielles et Humaines, Université de Valenciennes et du Hainaut-Cambrésis, Valenciennes, France;Laboratoire d'Informatique Fondamentale de Lille, Université des Sciences et Technologies de Lille, Villeneuve d'Ascq, France
Venue:
Journal of Heuristics
Year:
2007

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Abstract

In this paper, we present a solution method for a bi-objective vehicle routing problem, called the vehicle routing problem with route balancing (VRPRB), in which the total length and balance of the route lengths are the objectives under consideration. The method, called Target Aiming Pareto Search, is defined to hybridize a multi-objective genetic algorithm for the VRPRB using local searches. The method is based on repeated local searches with their own appropriate goals. We also propose an implementation of the Target Aiming Pareto Search using tabu searches, which are efficient meta-heuristics for the vehicle routing problem. Assessments with standard metrics on classical benchmarks demonstrate the importance of hybridization as well as the efficiency of the Target Aiming Pareto Search.