Effective inventory management is very critical to market success. The purpose of this paper is to formulate an integrated model for the location of warehouse, the allocation of retailers to the opened warehouses, and finding the perfect policy for inventory control to managing order quantity and safety stock level. The goal is to select the optimum numbers, locations, capacities of the opening warehouses and inventory policy so that all stochastic customer demands can be satisfied.
It is assumed that the location of plant has already been determined and the paper answers the following questions: what are the location decisions over the planning horizon? How retailers are allocated to the warehouses? What are the optimum capacities for the opened warehouses? What is the best inventory policy for this supply chain? What are the total minimum costs?
The model was developed as a non‐linear mixed integer programming and solved using Lagrange relaxation and sub‐gradient search for the location/allocation module and a procedure for the capacity planning module. The results for the randomly selected problems show that the average duality gap ranges are between 0.51 and 1.58 percent. Also, from the CPU time point of view, the performance of the proposed algorithm was very good.
The paper addresses an integrated location, allocation, and inventory decisions in the design of a supply chain distribution network. In addition sensitivity analyses are conducted to evaluate the effects of the multi‐capacity levels on some performance measures.
