An ant colony optimization metaheuristic hybridized with tabu search for open vehicle routing problems

Abstract

This paper studies the open vehicle routing problem (OVRP), in which the vehicle does not return to the starting depot after serving the last customer or, if it does, it must make the same trip in the reverse order. We propose an ant colony optimization-based metaheuristic for solving the OVRP. It is a ℳ𝒜𝒳–ℳℐ𝒩 ant system hybridized with tabu search, which is implemented in the hyper-cube framework. Additionally, a post-optimization strategy is incorporated to further improve the best-found solutions. We experimentally check the efficiency and effectiveness of the proposed algorithm by comparing its results with the existing methods in the literature, on a wide range of benchmark instances.

Keywords:

• distribution
• vehicle routing
• ant colony optimization
• heuristics

Acknowledgements

The authors would like to thank the editor and the referees for their valuable comments and suggestions that have greatly improved the quality of this paper. The work described in this paper was partially supported by a grant from City University of Hong Kong (Project No. 7002161).