Fuzzy Economic Order Quantity model for perishable items with stochastic demand, partial backlogging and fuzzy deterioration rate

Abstract

Most of the perishable inventory models in the literature assume that the rate of deterioration is a known constant. But in many practical situations, deterioration rate cannot be prescribed in advance; it may vary in a certain interval and hence can preferably be considered as a fuzzy number. The purpose of the paper is to develop and investigate an Economic Order Quantity (EOQ) model in the fuzzy sense by considering stochastic demand, partial backlogging and fuzzy deterioration rate. The proposed model is also extended to the case where the partial backlogging factor is assumed to be a fuzzy number. The minimum total cost and optimal order quantity are derived by defuzzifying the total cost through the signed distance method. Numerical examples are taken to demonstrate the developed models and compare the optimal results with those of the crisp models.