基于改进启发式算法的B2C电商物流库存路径优化方法  

Optimization Method for B2C E-commerce Logistics Inventory Path Based on Improved Heuristic Algorithm

作　　者：张丽琼 ZHANG Liqiong(Guangdong Vocational and Technical University of Light Industry,Guangzhou Guangdong 510150)

机构地区：[1]广东轻工职业技术大学,广东广州510150

出　　处：《软件》2024年第10期102-105,共4页Software

摘　　要：当前,B2C电商物流库存路径优化模型较为单一,优化的覆盖范围小,导致成本的标准差增加。为此,本文提出基于改进启发式算法的B2C电商物流库存路径优化方法的设计与分析。根据当前的路径优化需求进行物流点部署与B2C实时物流数据采集,结合改进启发式算法,扩大优化的覆盖范围。设计改进启发式测算B2C电商物流库存路径优化模型,采用自适应调整的方式完成路径优化处理。测试结果表明,相比于不确定需求下异构电动物流车辆的路径优化、碳排放和客户满意度下医药冷链物流配送路径优化,此次设计的改进启发式算法下B2C电商物流库存路径优化方法最终得出的成本标准差整体上呈现出下降的趋势,并逐渐保持平衡状态。说明在完整路径的优化后,对应的成本也更加可控,具有实际的应用价值。Currently,the optimization model for inventory routing in B2C e-commerce logistics is relatively single,with a small coverage area,resulting in an increase in the standard deviation of costs.Therefore,this article proposes the design and analysis of a B2C e-commerce logistics inventory path optimization method based on improved heuristic algorithms.Deploy logistics points and collect real-time B2C logistics data based on current path optimization requirements,combined with improved heuristic algorithms,to expand the coverage of optimization.Design and improve a heuristic calculation model for optimizing inventory paths in B2C e-commerce logistics,using adaptive adjustment to complete path optimization processing.The test results show that compared to the path optimization of heterogeneous electric logistics vehicles under uncertain demand,the optimization of pharmaceutical cold chain logistics distribution paths under carbon emissions and customer satisfaction,the cost standard deviation obtained by the improved heuristic algorithm for B2C e-commerce logistics inventory path optimization in this design shows an overall decreasing trend and gradually maintains a balanced state.After optimizing the complete path,the corresponding cost is also more controllable and has practical application value.

关 键 词：改进启发式算法 物流技术 电商物流 库存路径 B2C 流程优化 

分 类 号：U692[交通运输工程—港口、海岸及近海工程]