An efficient heuristic optimization algorithm for a two-echelon (R, Q) inventory system

This paper presents a two-echelon non-repairable spare parts inventory system that consists of one warehouse and m identical retailers and implements the reorder point, order quantity (R, Q) inventory policy. We formulate the policy decision problem in order to minimize the total annual inventory investment subject to average annual ordering frequency and expected number of backorder constraints. In order to solve the problem, we decompose the system by echelon and location, derive expressions for the inventory policy parameters, and develop an iterative heuristic optimization algorithm. Experimentation showed that our optimization algorithm is an efficient and effective method for setting the policy parameters in large-scale inventory systems.