考虑客户满意度的车辆路径优化及其算法研究

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摘要:

针对当前车辆路径问题中较少考虑客户满意度的情况,构建了基于模糊时间窗的车辆到达时间满意度函数和货物运输时长满意度函数,以最大化客户满意度和最小化配送总成本为目标建立VRPCCS数学模型.为了求解该问题,考虑到传统遗传算法存在依赖初始解、收敛速度较慢、容易陷入局部最优等缺点,设计改进的遗传算法与大规模邻域搜索算法相结合的混合算法进行求解,通过选取算例并与传统遗传算法进行对比,验证了模型和算法的可行性和有效性.实验仿真结果表明考虑客户满意度的物流配送方式不仅能够有效提升客户满意度,也能够降低物流企业配送成本以及车辆空载率,对于物流企业的车辆配送路径决策具有一定的参考意义.

In view of the fact that customer satisfaction is seldom considered in the current logistics distribution path problem,this paper constructs the satisfaction function of vehicle arrival time and the satisfaction function of cargo transportation duration based on the fuzzy time window,and establishes the VRPCCS mathematical model with the goal of maximizing customer satisfaction and minimizing the total distribution cost.Considering that the traditional genetic algorithm has the shortcomings of relying on the initial solution,the convergence rate is slow,and it is easy to fall into local optimization,the hybrid algorithm combining the improved genetic algorithm and the large-scale neighborhood search algorithm is designed to solve the problem,and the feasibility and effectiveness of the model and algorithm are verified by selecting the study example and comparing it with the traditional genetic algorithm.Experimental simulation results show that the logistics distribution method that considers customer satisfaction can not only effectively improve customer satisfaction,but also reduce the distribution cost and vehicle no-load rate of logistics enterprises,which has certain reference significance for the vehicle distribution path decision of logistics enterprises.

作者:

罗明亮袁鹏程

Luo Mingliang;Yuan Pengcheng(Business School,University of Shanghai for Science and Technology,Shanghai 200093,China)

机构地区:

上海理工大学管理学院

引用本文:

《betway官方app 学报（自然科学版）》 CAS 2024年第2期51-61,共11页

Journal of Henan Normal University(Natural Science Edition)

基金:

国家自然科学基金(71601118)。

关键词:

模糊时间窗客户满意度传统遗传算法混合算法