基于离散多元宇宙算法求解车辆路径问题

针对现实生活中车辆配送的实际情况以及客户对服务时间的具体要求，该文提出了一种离散多元宇宙算法来求解在模糊时间窗约束下的多配送中心车辆路径问题(MDVRPFTW)。以总成本最低、顾客满意度最大为多目标函数，针对MDVRPFTW构建出相应的数学模型。该算法在传统多元宇宙算法基础上，重新定义了在离散车辆路径问题下的更新策略。实验结果表明，该算法能更好地解决在模糊时间窗约束下的多配送中心车辆路径问题，优于其他几种对比算法，具有较强的寻优能力和应用价值。

Solving Vehicle Routing Problem with Fuzzy Time Window Based on Discrete Multiverse Algorithm

Aiming at the actual situation of vehicle distribution in real life and the specific requirements of customers for service time, this paper proposes a discrete multiverse algorithm to solve the multi-depot vehicle routing problem with fuzzy time windows (MDVRPFTW) under the constraint of fuzzy time windows. Taking the lowest total cost and the largest customer satisfaction as the multi-objective function, a corresponding mathematical model is constructed for MDVRPFTW. Based on the traditional multiverse algorithm, this algorithm redefines the update strategy under the discrete vehicle routing problem. The experimental results show that the algorithm can better solve the vehicle routing problem of multiple distribution centers under the fuzzy time window constraint, and the result is better than other comparison algorithms, which proves that it has a strong optimization ability and practical application value.