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An economic order quantity model considering different holding costs for imperfect quality items subject to fuzziness and learning

This paper extends an economic order quantity (EOQ) model for items with imperfect quality based on two different holding costs and learning considerations. This is one of the few attempts aiming at combining the EOQ model, learning theory, and fuzzy technique in solving an EOQ problem. In present research, a fuzzy model is developed in which both parameters and decision variables are fuzzified and represented by triangular fuzzy numbers (TFNs). The total profit per unit time is obtained using fuzzy arithmetic operations, and then defuzzified by the graded mean integration value (GMIV) method. Using Karush-Kuhn-Tucker (KKT) conditions, the optimal lot size is obtained from the defuzzified total profit per unit time function. A numerical example for investigating the behavior of the model in a fuzzy situation is presented, and directions for future study are proposed. Besides, the results of the developed fully fuzzy model are compared with some previous ones in the literature.