AN INNOVATIVE HEURISTIC FOR JOINT REPLENISHMENT PROBLEM WITH DETERMINISTIC AND STOCHASTIC DEMAND

Joint replenishment problem (JRP) is a common real problem which aims to minimize order cost and inventory holding cost. In this paper, classical, centralized and decentralized JRP models are discussed. An innovative heuristic to minimize the total cost is implemented for each model. This heuristic seeks to balance the order cost and the inventory holding costs. The results show that the innovative heuristic can best be implemented in the classical and decentralized models. For stochastic demand such as Poisson or Exponential distribution, the innovative heuristic can be implemented with the random variables which are generated by Monte Carlo simulation. [PUBLICATION ABSTRACT]