An Iterated Local Search heuristic for the Heterogeneous Fleet Vehicle Routing Problem

  • Authors:

  • Puca Huachi Penna;Anand Subramanian;Luiz Satoru Ochi

  • Affiliations:

  • Instituto do Noroeste Fluminense de Educação Superior, Universidade Federal Fluminense, Santo Antônio de Pádua, Brazil 28470-000 and Instituto de Computação, Universi ...;Departamento de Engenharia de Produção, Centro de Tecnologia, Universidade Federal da Paraíba, João Pessoa, Brazil 58051-970 and Instituto de Computação, Universidade ...;Instituto de Computação, Universidade Federal Fluminense, Niterói, Brazil 24210-240

  • Venue:
  • Journal of Heuristics
  • Year:
  • 2013

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Abstract

This paper deals with the Heterogeneous Fleet Vehicle Routing Problem (HFVRP). The HFVRP is $\mathcal{NP}$ -hard since it is a generalization of the classical Vehicle Routing Problem (VRP), in which clients are served by a heterogeneous fleet of vehicles with distinct capacities and costs. The objective is to design a set of routes in such a way that the sum of the costs is minimized. The proposed algorithm is based on the Iterated Local Search (ILS) metaheuristic which uses a Variable Neighborhood Descent procedure, with a random neighborhood ordering (RVND), in the local search phase. To the best of our knowledge, this is the first ILS approach for the HFVRP. The developed heuristic was tested on well-known benchmark instances involving 20, 50, 75 and 100 customers. These test-problems also include dependent and/or fixed costs according to the vehicle type. The results obtained are quite competitive when compared to other algorithms found in the literature.