Periodic Review Inventory Model Simulations for Imperfect Quality Items and Stochastic Demand

Abstract

Research on Economic Order Quantity (EOQ) models has been developed intensively to get practical models. One of the models is considering imperfect quality items where a fraction of imperfect quality items will be found after 100% screening a batch items. However, in many models, they only consider deterministic demand and there was no discussion about stochastic demand models. In this paper, stochastic demands are considered and we assume that a shipment is coming from a distant supplier and therefore it’s not feasible to replace the imperfect quality items with an additional order to the same supplier. The stochastic demand needs to be considered because of the fact that demand is uncertain. Since the model is hard to solve mathematically, simulation and evolutionary algorithm are used to solve the model. The results show that periodic review systems have less total inventory cost than continuous review system. The sensitivity analysis shows that s,S system is more robust than S,T system in difference standard deviation.