Stochastic Joint Replenishment Optimization under Joint Inbound Operational Cost

作     者：Xiaotian Zhuang Zhenyu Gao Yuli Zhang Qian Zhang Shengnan Wu Xiaotian Zhuang;Zhenyu Gao;Yuli Zhang;Qian Zhang;Shengnan Wu

作者机构：Department of Intelligent Supply ChainJD LogisticsBeijing100076China School of Management and EconomicsBeijing Institute of TechnologyBeijing100081China Yangtze Delta Region Academy of Beijing Institute of TechnologyJiaxingZhejiang314019China 

出 版 物：《Journal of Systems Science and Systems Engineering》 (系统科学与系统工程学报（英文版）)

年 卷 期：2023年第32卷第5期

页      面：531-552页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 

基　　金：supported by the National Natural Science Foundation of China under Grant numbers 72271029,71871023,72061127001,and 72201121 National Science and Technology Innovation 2030 Major program under Grant 2022ZD0115403 

主　　题：Stochastic joint replenishment stochastic demand inbound warehouse cost benders decomposition power-of-two policy 

摘      要：With e-commerce concentrating retailers and customers onto one platform,logistics companies(e.g.,JD Logistics)have launched integrated supply chain solutions for corporate customers(e.g.,online retailers)with warehousing,transportation,last-mile delivery,and other value-added *** platform’s concentration of business flows leads to the consolidation of logistics resources,which allows us to coordinate supply chain operations across different corporate *** paper studies the stochastic joint replenishment problem of coordinating multiple suppliers and multiple products to gain the economies of scale of the replenishment setup cost and the warehouse inbound operational *** this end,we develop stochastic joint replenishment models based on the general-integer policy(SJRM-GIP)for the multi-supplier and multi-product problems and further reformulate the resulted nonlinear optimization models into equivalent mixed integer second-order conic programs(MISOCPs)when the inbound operational cost takes the square-root ***,we propose generalized Benders decomposition(GBD)algorithms to solve the MISOCPs by exploiting the Lagrangian duality,convexity,and submodularity of the *** reduce the computational burden of the SJRM-GIP,we further propose an SJRM based on the power-of-two policy and extend the proposed GBD *** numerical experiments based on practical datasets show that the stochastic joint replenishment across multiple suppliers and multiple products would deliver 13∼20%cost savings compared to the independent replenishment benchmark,and on average the proposed GBD algorithm based on the enhanced gradient cut can achieve more than 90%computational time reduction for large-size problem instances compared to the Gurobi *** power-of-two policy is capable of providing high-quality solutions with high computational efficiency.