多元个性化需求驱动的最后一公里配送选址-路径研究  

Multiple personalized demands driven last mile delivery location-routing problem

作　　者：周林[1] 朱芳彬 代应[1] 景熠[1] 何彦东 ZHOU Lin;ZHU Fang-bin;DAI Ying;JING Yi;HE Yan-dong(College of Management,Chongqing University of Technology,Chongqing 400054,China;Graduate School at Shenzhen,Tsinghua University,Shenzhen 518055,China)

机构地区：[1]重庆理工大学管理学院,重庆400054 [2]清华大学深圳研究生院,广东深圳518055

出　　处：《控制与决策》2022年第10期2745-2752,共8页Control and Decision

基　　金：国家自然科学基金青年项目(71801025,71802034);重庆市教委科学技术研究项目(KJQN201801111);重庆市教委人文社科一般项目(18SKGH106,20SKGH160);重庆市社科规划一般项目(2017YBGL134);广东省基础与应用基础研究基金项目(2020A1515110785);重庆理工大学研究生创新项目(clgycx20203051)。

摘　　要：为提升最后一公里配送服务水平,基于现实场景中存在的自提、带时间窗的送货上门和柔性服务需求,提出多元个性化需求驱动的选址-路径问题.为了有效求解该问题,设计融合初始解构造算法、差异化邻域使用策略和自适应抖动机制的变邻域搜索算法.不同规模算例实验结果表明,改进的变邻域搜索算法具有较好的求解效率和鲁棒性.通过关键参数的敏感性分析发现,个性化需求比例与自提成本对运营成本影响显著,综合考虑这些因素开展配送系统设计具有较强的现实意义.Considering customer self-pick-up, home delivery with time window and flexible service demands in the last mile delivery, a location routing problem driven by multiple personalized demands is proposed to improve the service level.To solve the problem effectively, a variable neighborhood search algorithm is designed, which combines an initial solution construction algorithm, a differential neighborhood usage strategy and an adaptive shaking mechanism. Experimental results based on different scales of instances show that the improved variable neighborhood search algorithm has better solving efficiency and robustness. Through the sensitivity analysis of the key parameters, it is found that the proportion of personalized demands and pick-up cost have significant impacts on operating cost. It is of great practical significance to comprehensively consider these factors when designing the last mile delivery system.

关 键 词：最后一公里配送 个性化需求 选址-路径问题 改进变邻域搜索算法 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]