An inventory model for deteriorating items with nonlinear holding cost - Kamrani, Mohsen (2014)
Without any doubt, inventory management is a key factor in success of any organization. By broadening our view when we look at organizations as workings cogs of society and the role they play in the society, we will appreciate the effect of their success on peaple live both directly and indirectly. Due to the importance of inventory management, there have been a lot of works done by researchers, engineers, managers etc. They have developed different models and approaches to better analyze and manage the inventory by considering variuos factors such as fixed cost, holding cost, ordering cost, discounts and so forth. Many variations of models considered deterioration in their assumptions. Moreover, based on the research done by Ferguson el al, (2007) which actual data were applied from the national US grocery, it was concluded that in reality holding cost not linear. They showed involving nonlnear holding cost for perishable goods will reduce total cost up to 400% compared with when the company applies classic EOQ model as its policy. Undoubtedly considering nonlinear holding cost for perishable goods would make the model more applicable and practical to real situation. Based on above mentioned arguments, we suggest an inventory model for deteriorating items taking into account nonlinear holding cost. The model consists of three types of cost: ordering, holding and deteriorating costs which form the final objective function. It is proved that function is continuous and has a minimum. The minimum of the total cost can be found using a step by step algorithm. The algorithm is coded in MAtlab to hasten finding the solution. The model is validated by using numerical examples and comparison to classical EOQ by Harris (1913), nonlinear holding cost EOQ by Weiss (1982) and the simplified model of Chung ang Hunag (2007). The model shows lower costs compared to references models. Finally, in order to investigate the effects of changing model parameters on optimal answer and total cost, two sensitivity analyses are done.