Abstract: To solve the joint pricing of delivery options such as last-mile delivery methods and time slots,a nested Logit model was applied to describe customers' choice behavior of delivery options,including the attended home delivery,reception boxes delivery and different time slots.By considering the distribution cost minimum and the expected benefit maximum,the multi-objective joint pricing model of delivery options in urban distribution was established based on the mixed integer programming for analyzing the effect of delivery methods' scale factor on the joint pricing.The simulation analysis showed that there were clear Pareto fronts in RC201 and RC206 example;the customer substitution probability between different options was reduced and price adjustment had less impact on optimization goals as the scale factor of the attended home delivery increased,so the trend of attended home delivery pricing and time slot pricing was not clear.Owing to the fact that time slot constraint of reception box delivery was weaker than attended home delivery,time window pricing increasing was beneficial to achieve multi-objective Pareto improvement as the reception box delivery's scale factor increased.

Key words: urban distribution, last-mile delivery, time slot management, delivery option pricing, multi-objective optimization

摘要： 为解决末端交付方式和时间窗等可选配送服务选项的联合定价问题,考虑送货上门和自提柜两种交付方式,首先构建了考虑服务选项联合定价的嵌套Logit选择模型,描述了服务选项定价对顾客选择行为的影响;然后,考虑配送成本最小化和期望收益最大化,基于混合整数规划建立了城市配送服务选项多目标联合定价模型,着重分析了交付方式尺度因子对末端交付方式和时间窗联合定价的影响。仿真分析发现,RC201和RC206算例均存在明确的帕累托前沿;随着送货上门尺度因子的增加,顾客在选择不同服务选项时替代性降低,定价调整对优化目标影响较小,送货上门交付定价和时间窗定价的变化趋势不明显;由于自提柜交付时间窗约束弱于送货上门交付,随着自提柜交付尺度因子增大,提高时间窗定价有利于实现优化多目标帕累托改进。

关键词: 城市配送, 末端交付, 时间窗管理, 服务选项联合定价, 多目标优化