Volume 10 Issue 4 ( December )

This paper addresses the intractability in stochastic inventory systems due to frequent crossover of shipments. The present scenario due to volatile markets, presence of manifold ways to place orders globally, vacillating requirements of customers, climate disruptions, surge in demand of military equipments and medical devices lead to numerous orders are getting placed at small interval of times, due to which shipments are arrived in different order in which they were booked. The fast-moving items are highly susceptible to order crossover. In this paper, based on the ratio of ordering cost to inventory carrying charge, fast moving items are categorized as fast movers not ordered enough and fast movers frequently ordered. The datasets are used for developing regression equations for optimal total inventory cost, order quantity and safety stock factor from the results of factorial experiments. The first group of regression equations are handy for decision systems lead to essentials items and second one is applicable in decision systems for discretionary products. The regression equations will help the practitioners to compute the right optimal quantity, estimate the correct inventory cost and compute safety stock factor, that will help their industry sustainability in the global world and provide a competitive edge over their competitors.

Keywords: Order Crossover; Fast-moving; Regression; Inventory; Sustainability