A GRASP with evolutionary path relinking for the truck and trailer routing problem

  • Authors:

  • Juan G. Villegas;Christian Prins;Caroline Prodhon;Andrés L. Medaglia;Nubia Velasco

  • Affiliations:

  • Laboratoire d'Optimisation des Systèmes Industriels (LOSI), Institut Charles Delaunay, Université de Technologie de Troyes, BP 2060, 10010 Troyes Cedex, France and Centro para la Optimiz ...;Laboratoire d'Optimisation des Systèmes Industriels (LOSI), Institut Charles Delaunay, Université de Technologie de Troyes, BP 2060, 10010 Troyes Cedex, France;Laboratoire d'Optimisation des Systèmes Industriels (LOSI), Institut Charles Delaunay, Université de Technologie de Troyes, BP 2060, 10010 Troyes Cedex, France;Centro para la Optimización y Probabilidad Aplicada (COPA), Departamento de Ingeniería Industrial, Universidad de los Andes, A.A. 4976, Bogotá D.C., Colombia;Centro para la Optimización y Probabilidad Aplicada (COPA), Departamento de Ingeniería Industrial, Universidad de los Andes, A.A. 4976, Bogotá D.C., Colombia

  • Venue:
  • Computers and Operations Research
  • Year:
  • 2011

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Abstract

In the truck and trailer routing problem (TTRP) a heterogeneous fleet composed of trucks and trailers has to serve a set of customers, some only accessible by truck and others accessible with a truck pulling a trailer. This problem is solved using a route-first, cluster-second procedure embedded within a hybrid metaheuristic based on a greedy randomized adaptive search procedure (GRASP), a variable neighborhood search (VNS) and a path relinking (PR). We test PR as a post-optimization procedure, as an intensification mechanism, and within evolutionary path relinking (EvPR). Numerical experiments show that all the variants of the proposed GRASP with path relinking outperform all previously published methods. Remarkably, GRASP with EvPR obtains average gaps to best-known solutions of less than 1% and provides several new best solutions.