An evolutionary algorithm for the vehicle routing problem with route balancing |
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Authors: | Nicolas Jozefowiez Frédéric Semet El-Ghazali Talbi |
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Institution: | 1. Laboratoire d’Informatique Fondamentale de Lille, Université des Sciences et Technologies de Lille, 59655 Villeneuve d’Ascq, France;2. Laboratoire d’Automatique, de Mécanique et d’Informatique industrielles et Humaines, Université de Valenciennes et du Hainaut-Cambrésis, 59313 Valenciennes Cedex 9, France |
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Abstract: | In this paper, we address a bi-objective vehicle routing problem in which the total length of routes is minimized as well as the balance of routes, i.e. the difference between the maximal route length and the minimal route length. We propose a meta-heuristic method based on an evolutionary algorithm involving classical multi-objective operators. To improve its efficiency, two mechanisms, which favor the diversification of the search, have been added. First, an elitist diversification mechanism is used in cooperation with classical diversification methodologies. Second, a parallel model designed to take into account the elitist diversification is proposed. Our method is tested on standard benchmarks for the vehicle routing problem. The contribution of the introduced mechanisms is evaluated by different performance metrics. All the experimentations indicate a strict improvement of the generated Pareto set. |
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Keywords: | Routing Multi-objective optimization Genetic algorithms Parallel algorithms |
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