This study presents a two-echelon inventory routing problem (2E-IRP) with an end-of-tour replenishment (ETR) policy whose distribution network consists of a supplier, several distribution centers (DCs) and several ret...This study presents a two-echelon inventory routing problem (2E-IRP) with an end-of-tour replenishment (ETR) policy whose distribution network consists of a supplier, several distribution centers (DCs) and several retailers on a multi-period planning horizon. A formulation of the problem based on vehicle indices is proposed in the form of a mixed integer linear program (MILP). The mathematical model of the problem is solved using a branch and cut (B&C) algorithm. The results of the tests are compared to the results of a branch and price (B&P) algorithm from the literature on 2E-IRP with a classical distribution policy. The results of the tests show that the B&C algorithm solves 197 out of 200 instances (98.5%). The comparison of the B&C and B&P results shows that 185 best solutions are obtained with the B&C algorithm on 197 instances (93.9%). Overall, the B&C algorithm achieves cost reductions ranging from 0.26% to 41.44% compared to the classic 2E-IRP results solved with the B&P algorithm, with an overall average reduction of 18.08%.展开更多
A replenishment decision-making model for supply-hub is firstly established from the angle of supplier, and optimal replenishment decision of the supplier is analyzed. Then, inventory optimization model for supply-hub...A replenishment decision-making model for supply-hub is firstly established from the angle of supplier, and optimal replenishment decision of the supplier is analyzed. Then, inventory optimization model for supply-hub is formulated from the angle of the manufacturer, and the optimization algorithm for obtaining optimal inventory levels is given. The result shows that liability period decides the share of the inventory cost between two sides in supply chain. With the increase of liability period, the service level has been quickly reduced even though the manufacturer's cost has been cut down by transferring the inventory cost to the supplier. As to the safety inventory, if the lower bound of components safety inventory increases, the supplier's cost will rise up more slowly than the liability period does, while the service levels increases as the safety inventory's lower bound is raised.展开更多
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 warehous...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 services.The platform’s concentration of business flows leads to the consolidation of logistics resources,which allows us to coordinate supply chain operations across different corporate customers.This 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 cost.To 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 form.Then,we propose generalized Benders decomposition(GBD)algorithms to solve the MISOCPs by exploiting the Lagrangian duality,convexity,and submodularity of the sub-problems.To 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 algorithms.Extensive 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 solver.The power-of-two policy is capable of providing high-quality solutions with high computational efficiency.展开更多
文摘This study presents a two-echelon inventory routing problem (2E-IRP) with an end-of-tour replenishment (ETR) policy whose distribution network consists of a supplier, several distribution centers (DCs) and several retailers on a multi-period planning horizon. A formulation of the problem based on vehicle indices is proposed in the form of a mixed integer linear program (MILP). The mathematical model of the problem is solved using a branch and cut (B&C) algorithm. The results of the tests are compared to the results of a branch and price (B&P) algorithm from the literature on 2E-IRP with a classical distribution policy. The results of the tests show that the B&C algorithm solves 197 out of 200 instances (98.5%). The comparison of the B&C and B&P results shows that 185 best solutions are obtained with the B&C algorithm on 197 instances (93.9%). Overall, the B&C algorithm achieves cost reductions ranging from 0.26% to 41.44% compared to the classic 2E-IRP results solved with the B&P algorithm, with an overall average reduction of 18.08%.
基金Projects(71102174,70971036) supported by the National Natural Science Foundation of ChinaProject(9123028) supported by the Beijing Natural Science Foundation,China+3 种基金Project(20111101120019) supported by the Specialized Research Fund for Doctoral Program of Higher Education of ChinaProject(11JGC106) supported by the Beijing Philosophy&Social Science Foundation of ChinaProjects(NCET-10-0048,NCET-10-0043) supported by the Program for New Century Excellent Talents in Universities of ChinaProject(2010YC1307) supported by the Excellent Young Teacher in Beijing Institute of Technology of China
文摘A replenishment decision-making model for supply-hub is firstly established from the angle of supplier, and optimal replenishment decision of the supplier is analyzed. Then, inventory optimization model for supply-hub is formulated from the angle of the manufacturer, and the optimization algorithm for obtaining optimal inventory levels is given. The result shows that liability period decides the share of the inventory cost between two sides in supply chain. With the increase of liability period, the service level has been quickly reduced even though the manufacturer's cost has been cut down by transferring the inventory cost to the supplier. As to the safety inventory, if the lower bound of components safety inventory increases, the supplier's cost will rise up more slowly than the liability period does, while the service levels increases as the safety inventory's lower bound is raised.
基金supported by the National Natural Science Foundation of China under Grant numbers 72271029,71871023,72061127001,and 72201121National Science and Technology Innovation 2030 Major program under Grant 2022ZD0115403.
文摘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 services.The platform’s concentration of business flows leads to the consolidation of logistics resources,which allows us to coordinate supply chain operations across different corporate customers.This 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 cost.To 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 form.Then,we propose generalized Benders decomposition(GBD)algorithms to solve the MISOCPs by exploiting the Lagrangian duality,convexity,and submodularity of the sub-problems.To 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 algorithms.Extensive 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 solver.The power-of-two policy is capable of providing high-quality solutions with high computational efficiency.
