基于供需匹配优化的多货品可拆分车辆路径问题  

Multi-commodity Split Vehicle Routing Problem Based on Supply and Demand Matching Optimization

作　　者：史铭 莫思敏 SHI Ming;MO Simin(School of Economics and Management,Taiyuan University of Science and Technology,Taiyuan 030024,China)

机构地区：[1]太原科技大学经济与管理学院,山西太原030024

出　　处：《物流科技》2025年第3期21-25,共5页Logistics Sci Tech

摘　　要：针对供应链上下游企业原料生产运输问题,提出了供需匹配优化策略,并将部分客户对不同原料的需求分批次配送,可以确保满足客户需求并降低车辆空载率、提高运输效率,建立了以车辆固定成本和行驶成本之和最小为目标的取送货车辆路径优化模型。采用遗传算法进行求解,设计了供需匹配对编码策略和车辆路径调整策略,可以增强全局搜索能力,更有可能获得最优解。通过算例分析得出最小总成本和最优车辆路径,并验证了文章匹配策略和需求拆分策略的有效性,研究成果对生产运输企业的实际运营具有一定的参考价值。Aiming at the production and transportation problem of raw materials for upstream and downstream enterprises in the supply chain,the optimization strategy of supply and demand matching was proposed,and some customers'demand for different raw materials was distributed in batches,which could ensure that customer demand could be met,vehicle empty load rate could be reduced,and transportation efficiency could be improved.A pickup and delivery vehicle routing optimization model aiming at the minimum sum of fixed cost and running cost of vehicles was established.Genetic algorithm is used to solve this problem.The supply and demand matching pair coding strategy and vehicle routing adjustment strategy are designed,which can enhance the global search ability and more likely to obtain the optimal solution.The minimum total cost and the optimal vehicle routing are obtained through experiments and the effectiveness of the matching strategy and demand splitting strategy is verified.The research results have certain reference value for the actual operation of production and transportation enterprises.

关 键 词：供需匹配优化 多货品可拆分 车辆路径 遗传算法 

分 类 号：F253[经济管理—国民经济]