1.Chongqing University of Technology;2.Graduate school at Shenzhen, Tsinghua University
National Nature Science Fundation of China
为提升最后一公里配送服务水平, 本文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, 设计了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. Sensitivity analysis of the key parameters 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.