A Hybrid Genetic Algorithm for Multidepot and Periodic Vehicle Routing Problems

  • Authors:

  • Thibaut Vidal;Teodor Gabriel Crainic;Michel Gendreau;Nadia Lahrichi;Walter Rei

  • Affiliations:

  • CIRRELT and Département d'informatique et de recherche opérationnelle, Université de Montréal, Montréal, Quebec H3C 3J7, Canada;CIRRELT and Département de management et technologie, École des sciences de la gestion, University of Quebec in Montréal, Montréal, Quebec H3C 3P8, Canada;CIRRELT and Département de mathématiques et génie industriel, École Polytechnique, Montréal, Quebec H3C 3A7, Canada;CIRRELT and Département de mathématiques et génie industriel, École Polytechnique, Montréal, Quebec H3C 3A7, Canada;CIRRELT and Département de management et technologie, École des sciences de la gestion, University of Quebec in Montréal, Montréal, Quebec H3C 3P8, Canada

  • Venue:
  • Operations Research
  • Year:
  • 2012

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Abstract

We propose an algorithmic framework that successfully addresses three vehicle routing problems: the multidepot VRP, the periodic VRP, and the multidepot periodic VRP with capacitated vehicles and constrained route duration. The metaheuristic combines the exploration breadth of population-based evolutionary search, the aggressive-improvement capabilities of neighborhood-based metaheuristics, and advanced population-diversity management schemes. Extensive computational experiments show that the method performs impressively in terms of computational efficiency and solution quality, identifying either the best known solutions, including the optimal ones, or new best solutions for all currently available benchmark instances for the three problem classes. The proposed method also proves extremely competitive for the capacitated VRP.