A tabu search with vocabulary building approach for the vehicle routing problem with split demands

  • Authors:

  • Rafael E. Aleman;Raymond R. Hill

  • Affiliations:

  • BIE Department, Wright State University, 3640 Colonel Glenn Hwy, Dayton, OH 45435, USA.;Air Force Institute of Technology, Wright-Patterson AFB, Dayton OH 45433, USA

  • Venue:
  • International Journal of Metaheuristics
  • Year:
  • 2010

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Abstract

In the vehicle routing problem (VRP) a fleet of vehicles with limited capacity is utilised to supply the demand of a set of customers located around a unique depot while minimising the total travelled distance. All customer demands are supplied and customers are visited by exactly one vehicle. In the split delivery vehicle routing problem (SDVRP), customers can be visited by more than one vehicle meaning their demands can be split among multiple vehicles. This paper presents a learning procedure, called tabu search with vocabulary building approach (TSVBA) for solving the SDVRP. TSVBA is a population-based search approach that uses a set of solutions to find attractive solution attributes with which to construct new solutions. As the search progresses, the solution set evolves; better solutions move into the set while bad solutions are removed. The proposed learning procedure was tested on benchmark instances and performed well when its solutions are compared to those reported in the literature. New best solutions are obtained on some benchmark problems available.