Retailer’s EOQ model in fuzzy annual demand inventory with limited storage space under partially permissible delay in payments

Abstract

Traditionally, most of the publications assume that the annual demand is deterministic. However, there are many uncertain factors in real world. So we use the signed distance, a ranking method for fuzzy numbers to estimate the annual demand, and this paper wants to investigate optimal retailer’s lot-sizing policy with two warehouses under partially permissible delay in payments within the economic order quantity (EOQ) framework. In this paper, we want to extend that fully permissible delay in payments to the supplier would offer the retailer partially permissible delay in payments. That is, the retailer must make a partial payment to the supplier when the order is received. Then the retailer must pay off the remaining balance at the end of the permissible delay period. In addition, we want to add the assumption that the retailer’s storage space is limited. That is, the retailer will rent the warehouse to store these exceeding items when the order quantity is larger than retailer’s storage space. Under these conditions, we model the retailer’s inventory system as a cost minimization problem to determine the retailer’s optimal cycle time and optimal order quantity. Three theorems are developed to efficiently determine the optimal replenishment policy for the retailer. Finally, numerical examples are given to illustrate these theorems and obtained a lot of managerial insights.