JOINT REPLENISHMENT STRATEGIES IN SUPPLY CHAINS

Byung-Chul Cha

In inventory systems cost savings can be achieved by coordinating the replenishment of several items. The joint replenishment problem (JRP) deals with problem of coordinating the replenishment of a group of items that may be jointly ordered from a single supplier. Although the joint replenishment problem has received considerable attention from researchers during the last three decades, there was few research to extend it. This is the motivation of our research.
We extended the JRP to consider resource restriction, quantity discounts, a multi-supplier system and a one-warehouse, n-retailer system. Two types of solution method are used to solve these problems. One is an iterative algorithm using the optimality conditions of decision variables and the other is a genetic algorithm. For the iterative algorithm, we modified RAND (Kaspi and Rosenblatt, 1991) which is very efficient to solve the general joint replenishment problem. For the genetic algorithm, we used a global searching ability to find the optimal values of decision variables which have only integer values. For a decision variable which has a real number, the optimality condition was also used as in the iterative algorithm.