Abstract: In order to analyze the effect of the correlation between the last-mile delivery and time slot existing in the customer choice procedure of urban distribution service on the operational decisions, such as reception box locating, time slot allocating and vehicle routing, a nested Logit model was used to quantify the customer's choice of delivery service options, and a two-tier nested Logit selection model for urban delivery was proposed. Then a multi-objective optimization model integrated with reception box locating, time slot allocating and vehicle routing was constructed in the purpose of maximizing the delivery amount and minimizing the delivery cost. At last, a Multi-Objective Particle Swarm Optimization (MOPSO) algorithm was constructed to solve this model based on non-dominance sorting, adaptive grid and crowding distance sorting. The analysis shows that, as the attended-home-delivery independence parameter is gradually increased, the substitution of customer demand in different time slots is smaller, the optimal solutions tend to improve the delivery punctuality with increasing the delivery amount, whether it is to minimize the cost or to maximize the number of delivery; on the contrary, with the increase of the reception-box independence parameter, the optimal solutions will decrease the delivery punctuality with reducing the delivery amount.

Key words: urban distribution, nested Logit model, last-mile delivery, time slot management, reception box locating, route planning

摘要： 为了分析城市配送中顾客选择末端交付方式和配送时间窗的相关性对自提柜选址、时间窗分配与路径规划等运营决策的影响，首先使用嵌套Logit选择模型量化顾客对配送服务选项的选择行为，提出了城市配送两层嵌套Logit选择模型；然后以配送数量最大化和配送成本最小化为目标，建立了自提柜选址-时间窗分配-路径规划集成优化模型；最后采用非支配排序、动态网格和拥挤距离等技术，构建了多目标粒子群优化（MOPSO）算法进行仿真分析，获取了末端交付方式和配送时间窗相关性对运营决策的影响。研究表明：随着送货上门服务尺度因子逐渐增大，顾客需求在不同配送时间窗之间的替代性变小，无论是追求配送成本最小化、还是追求配送数量最大化，获取的最优方案均倾向于提高配送准时性，配送数量逐渐上升；相反，随着自提柜服务尺度因子逐渐增大，不同于送货上门服务，获取的最优方案倾向于降低配送准时性，配送数量逐渐下降。

关键词: 城市配送, 嵌套Logit选择模型, 末端交付, 时间窗管理, 自提柜选址, 路径规划