关键词: 车辆路径问题, 模糊需求, 模糊时间窗, 混合遗传算法, 擂台法则

Abstract: Considering the vehicle routing problem with fuzzy demand and fuzzy time window, this paper designed a multi-objective fuzzy chance constrained model, with the objectives of minimizing the total travel distance and the number of vehicles, and maximizing the satisfaction of average customers. In order to improve the diversity of the population, the crossover operator was improved. Based on the introduction of the local search algorithm and Arena’s principle, a hybrid genetic algorithm was designed to solve the multi-objective vehicle routing problem. Experiments of VRPTW standard examples not only show that the algorithm can effectively solve the vehicle routing problem with time windows, but also show the influence of the dispatcher preference index on the decision objective. The research results can provide a way for solving the vehicle routing problem with fuzzy demand and time window, and guidance for actual distribution path planning.

Key words: vehicle routing problem, fuzzy demand, fuzzy time window, hybrid genetic algorithm, Arena's principle