Abstract
The paper presents a two-echelon inventory-transportation problem in Vendor Managed Inventory (VMI) system. We consider a distribution system composed with single supplier, single distribution center and multiple retailers. Single kind of products are required to deliver from the manufacturer through distribution center to the retailers within soft time window. The objective of the problem is to minimize total logistics cost in the distribution network, including inventory cost, distribution cost, and time penalty cost. The upper echelon model focuses on minimizing inventory cost while the lower echelon model on vehicle routing problem. A mixed algorithm is designed to solve the problem with simulated annealing and ant colony with local search. The solution of upper and lower echelon model are substituted into each other based on the mixed algorithm step by step to get the optimization solutions. Computational experiments are executed to compare the performance of independent and integrated inventory-transportation optimization from the dimension of to verify the effectiveness of the model and the algorithms.
Highlights
Vendor-Managed Inventory (VMI) has been a widely and successfully practiced strategy in supply chain management, aiming at reducing cost and adding value
Suppliers manages the inventory for the retailers including the decisions of replenishing, delivering and inventory management for supply chains implementing VMI (Lee and Seungjin [1]; Simchi-Levi et al [2])
We introduce penalty function to add the restriction of soft time window with the formulation
Summary
Vendor-Managed Inventory (VMI) has been a widely and successfully practiced strategy in supply chain management, aiming at reducing cost and adding value. Tempelmeier and Bantel [13] developed a multi-objective model composed of single supplier and multiple customers optimizing inventory and transportation jointly under stochastic demand. VOLUME 7, 2019 products under stochastic demand They considered a particular cost structure with additional vehicles in delivery process, and they proposed a new policy that could make different items replenishing independently. Zhao et al [30] extended classical VRP considering the factor of vehicle’s travel speed Such bi-objective problem has been studied on integrated optimization on transportation industry [31]–[34]. There are gap on previous research that simultaneously considering the factor of distribution period, delivery bunch and vehicle routing in single supplier and multiple customers.
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