Resolving the VRPTW using an improved hybrid genetic algorithm

Authors

  • Sami Mnasri Université de Toulouse, CNRS-IRIT Laboratory, IRT group
  • Fatma Abbes Institut Supérieur de Gestion de Tunis, SOIE Laboratory

Keywords:

Vehicles Routing Problem, VRPTW, Optimization, BCRC, NSGAII

Abstract

This paper proposes an approach which is based on a multi objective genetic algorithm to resolve the vehicles routing problem with time windows (VRPTW). The context of this problem is to plan a set of routes to serve heterogeneous demands respecting several constraints (only one depot, vehicles limited capacity, windows of time). We used an approach based on a multi-objective optimization to resolve this problem. The criteria to be optimized are the number of used vehicles and the total required distance. We propose a method of resolution which is based on a hybridization of a genetic algorithm NSGAII (Not dominated Sorting Genetic Algorithm II) and the BCRC algorithm (Best Cost Route Crossover).

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Published

2014-07-01

How to Cite

Sami Mnasri, & Fatma Abbes. (2014). Resolving the VRPTW using an improved hybrid genetic algorithm. Journal of Network and Innovative Computing, 2, 9. Retrieved from https://cspub-jnic.org/index.php/jnic/article/view/64

Issue

Vol. 2 (2014)

Section

Original Article

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