Preserving population diversity for the multi-objective vehicle routing problem with time windows

  • Authors:

  • Abel Garcia-Najera

  • Affiliations:

  • University of Birmingham, Birmingham, United Kingdom

  • Venue:
  • Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
  • Year:
  • 2009

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Abstract

The Vehicle Routing Problem's main objective is to find the lowest-cost set of routes to deliver goods to customers, which have a service time window, using a fleet of identical vehicles with restricted capacity. We consider the simultaneous minimization of the number of routes along with the total travel distance. Although previous research has used evolutionary methods for solving this problem, only a few of them have concentrated on the optimization of more than one objective, and none of them has considered the similarity of solutions. We propose and analyze one simple and straightforward method to measure similarity, which is incorporated into an evolutionary algorithm to solve the multi-objective problem. Results show that when we use the similarity measure to select one of the parents for crossover, solutions are spread over a wider area in the search space than when it is not used. Additionally, our solutions result to be competitive or better than others previously published.