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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. To nullify the issues of imprecise nature of demand rate in business organization, fuzzy method has been utilized here. The analytical solution to the optimization problem, where demand is formulated as a triangular fuzzy number, is obtained. The objective of this paper is to find the best credit policy for the retailer when the items are deteriorating and imperfect in nature. Credit policy is devised with learning and inflation under fuzzy environment. The findings provide important managerial insights to the retailers for deciding the perfect ordering policy under varying situations. For example, (1) when the defective items increases in the order lot, then the retailers should be more vigilant while ordering; (2) for highly deteriorating items the retailers should order more frequently; (3) when the value of net discount inflation rate increases, cycle length, screening rate, order quantity, as well as total fuzzy profit decrease; (4) if the value of learning rate increases, initially, cycle length, screening rate, order quantity as well as total fuzzy profit increase, and after some time, these values will become stable due to the learning effect. 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.

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