An adaptive large neighborhood search with multi-deletion operators for multi-depot green vehicle routing problem with time windows

Abstract

In this paper, we proposed an adaptive large neighborhood search algorithm with multiple deletion operators (ALNS-MDO) to solve the multi-depot green vehicle routing problem with time windows, considering multi-depot sharing and driver working time limit constraints (MDGVRPTW-DTL). In ALNS-MDO, we used multiple deletion operators to destroy routes in each search cycle. At the same time, the number of customer nodes deleted in each deletion operator operation in each search cycle was adaptively selected. Finally, an operator weight coefficient reset strategy was added to avoid premature convergence of the algorithm. We conducted a comparative experiment between ALNS-MDO and five state-of-the-art optimization algorithms. The experimental results show that ALNS-MDO achieves better optimization results in a large number of experimental instances, which proves that ALNS-MDO has extensive advantages in optimization ability. At the same time, the necessity of each algorithm improvement and the stability of algorithm optimization ability have also been proven.