Self-organization and evolution combined to address the vehicle routing problem

Authors:
Jean-Charles Créput;Abderrafiaâ Koukam
Affiliations:
Systems and Transportation Laboratory, University of Technology of Belfort-Montbeliard, Belfort, France;Systems and Transportation Laboratory, University of Technology of Belfort-Montbeliard, Belfort, France
Venue:
EA'07 Proceedings of the Evolution artificielle, 8th international conference on Artificial evolution
Year:
2007

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Abstract

The paper deals with a self-organizing system in a evolutionaryframework applied to the Euclidean Vehicle Routing Problem (VRP).Theoretically, self-organization is intended to allow adaptation to noisy data aswell as to confer robustness according to demand fluctuation. Evolutionthrough selection is intended to guide a population based search toward near-optimal solutions. To implement such principles to address the VRP, theapproach uses the standard self-organizing map algorithm as a main operatorembedded in a evolutionary loop. We evaluate the approach on standardbenchmark problems and show that it performs better, with respect to solutionquality and/or computation time, than other self-organizing neural networks tothe VRP presented in the literature. As well, it substantially reduces the gap tosome classical Operations Research heuristics.