Impact of Learning on the Inventory Model of Deteriorating Imperfect Quality Items With Inflation and Credit Financing Under Fuzzy Environment

Abstract

The present paper contributes to a set of models capturing economic order quantity with learning effect and fuzzy environment for decaying defective quality items under the inflation condition and credit financing. In real-life situations, the demand is uncertain and is controlled with fuzzy numbers. When each item goes through inspection process, the screening rate is assumed to be more than the demand rate otherwise shortages may occur and this consideration also helps one to meet their demand parallel to the screening process, out of the items which are of perfect quality. Further, the defective items are sold immediately after the screening process as a single lot at a discounted price. Further, the fraction of defective items follows the S-shaped learning curve. An expression for the total fuzzy profit of the retailer has been de-fuzzified with the help of a signed distance method and maximizes the cycle length. Conclusively, sensitive analysis has been presented on the various effective parameters of the inventory model.