Adaptive Path Relinking for Vehicle Routing and Scheduling Problems with Product Returns

  • Authors:

  • Christos D. Tarantilis;Afroditi K. Anagnostopoulou;Panagiotis P. Repoussis

  • Affiliations:

  • Operations Research and Decision Systems Centre, Management Science Laboratory, Department of Management Science and Technology, Athens University of Economics and Business, Athens, Greece GR 1043 ...;Operations Research and Decision Systems Centre, Management Science Laboratory, Department of Management Science and Technology, Athens University of Economics and Business, Athens, Greece GR 1043 ...;Howe School of Technology Management, Stevens Institute of Technology, Hoboken, New Jersey 07030

  • Venue:
  • Transportation Science
  • Year:
  • 2013

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Abstract

This paper deals with one-to-many-to-one vehicle routing and scheduling problems with pickups and deliveries and studies the effect of various backhauling strategies. Initially, focus is given on problem instances with clustered backhauls where all delivery customers must be visited before pickup customers. Afterward, operational settings with mixed backhauls and varying visiting sequence restrictions with respect to the capacity of the vehicles are examined. The proposed solution method evolves a set of reference solutions on the basis of a novel Adaptive Path Relinking framework. The latter encompasses an adaptive multisolution recombination procedure to generate provisional solutions based on the recurrence of particular solution attributes. On return, these solutions are used as guiding points for performing search trajectories from initial reference solutions via tunneling. Computational results on benchmark data sets of the literature illustrate the competitiveness and robustness of the proposed approach compared to state-of-the-art solution methods for well-known vehicle routing and scheduling problems. Finally, various experiments are also reported to demonstrate the economic effect of different mixing levels and densities of linehaul and backhaul customers.