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

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.