An Effective Heuristic for Multidepot Low-Carbon Vehicle Routing Problem

Abstract

Low-carbon economy has been a hot research topic in recent years. This paper firstly considers the vehicle load weight, the key factors affecting the fuel consumption, to establish the fuel consumption model, and then constructs the vehicle routing planning model in the last mile delivery with multiple depots within time windows. In order to solve this problem, we improve the classical fruit fly algorithm which is easy to fall into the local optimum, and the improved fruit fly optimization algorithm is designed and integrated with genetic algorithm. Computational results show that our solution approach is capable of solving instances with up to 48 customers and 4 different depots. The effectiveness and efficiency of the model and multigroup fruit fly algorithm are verified through case study.