大规模突发事件下基于“派单+抢单”的平台配送模式优化模型  

Optimization Model and Algorithm for Platform-based"Dispatch+Grab-order"Delivery Mode under Large-scale Disruption Events

作　　者：刘柳 孟令鹏 LIU Liu;MENG Lingpeng(Business School,Wuhan Huaxia Institute of Technology,Wuhan 430223,China;China Institute of FTZ Supply Chain,Shanghai Maritime University,Shanghai 201306,China)

机构地区：[1]武汉华夏理工学院商学院,湖北武汉430223 [2]上海海事大学中国(上海)自贸区供应链研究院,上海201306

出　　处：《物流科技》2025年第1期34-38,62,共6页Logistics Sci Tech

基　　金：国家自然科学基金资助项目(72474128、71974122)。

摘　　要：大规模突发事件会导致平台配送面临订单模糊、车辆配送路网复杂、取送货序列配对困难等现实问题。文章提出一种基于平台“派单+抢单”的组合运营模式,充分发挥派单模式高效匹配配送员-订单,以及抢单模式有效提升平台配送灵活性的优势,以配送成本最低、客户满意度最高为优化目标,建立多目标混合整数规划模型,并设计基于GA-SA的混合进化算法对配货员的配送路径进行合理规划,保障商家、客户多对关系下的货物取送有序。数值实验表明,所设计的优化算法能够有效解决抢单模式下的即时配送车辆路径问题,具有很好的效率和应用性。Large-scale disruption events can cause platform delivery to face realistic problems such as order ambiguity,complex vehicle delivery network,and difficulty in matching pickup and delivery sequences.This study addresses the combined"dispatch+grab-order"operational model,leveraging the efficient courier-order matching of the dispatch model and the enhanced delivery flexibility of the grab-order model.With the dual optimization goals of minimizing delivery costs and maximizing customer satisfaction,an optimization model is developed to ensure orderly pick-up and delivery in multi-seller and multi-customer relationships.A hybrid GA-SA evolutionary algorithm is designed to effectively plan delivery routes for couriers.Numerical experiments show that the proposed optimization algorithm can efficiently solve real-time vehicle routing problems.

关 键 词：大规模公共事件 即时配送 多目标规划模型 混合进化算法 

分 类 号：F252.14[经济管理—国民经济]