A hybridization of granular adaptive tabu search with path relinking for the multi-depot open vehicle routing problem

• Published in: Egyptian informatics journal Vol. 24; no. 4; p. 100420
• Main Authors: Shao, Wenhan, Xiao, Tuanyue, Su, Zhouxing, Ding, Junwen, Lü, Zhipeng
• Format: Journal Article
• Language: English
• Published: Elsevier 01.12.2023
• Subjects: Adaptive neighborhood selection; Granular neighborhoods; Multi-depot open vehicle routing problem; Path relinking; Solution-based tabu search
• ISSN: 1110-8665; 2090-4754
• DOI: 10.1016/j.eij.2023.100420

The multi-depot open vehicle routing problem (MDOVRP) differs from the classical VRP in that there is more than one depot and the vehicle does not need to return to a depot after serving the last customer. For solving this challenging problem, we propose a hybrid metaheuristic algorithm (GATS-PR) which integrates the granular adaptive tabu search with path relinking. The main contributions of this work consist of introducing a solution-based tabu search technique in granular tabu search, designing an adaptive neighborhood selection method for the large neighborhoods with 22 kinds of move types, and adopting path relinking with a new similarity definition to the MDOVRP for the first time. Computational results on 24 public instances demonstrate that GATS-PR outperforms the previous state-of-the-art algorithms in the literature. Specifically, GATS-PR improved and matched the previous best known results on 4 and 19 instances, respectively.