Decision making in fuzzy reasoning to solve a backorder economic order quantity model

Abstract

Fuzzy reasoning is the subject of fuzzy system where the fuzzy set is characterized by the randomization of the variable associated in the fuzzy set itself. It is the first-time application of fuzzy reasoning over the backorder economic order quantity (EOQ) inventory management problem. We first define the fuzzy reasoning membership function through the use of L-fuzzy number and possibility theory on fuzzy numbers. Considering the holding cost, set up cost, backordering cost and demand rate as reasoning based fuzzy number, we have constructed a dual fuzzy mathematical problem. Then this problem has been solved over the dual feasible space which is associated to the aspiration level and the fuzzy approximation constant. Numerical study reveals the superiority of the proposed method with respect to the crisp solution as well as general fuzzy solution. Sensitivity analysis and graphical illustrations have also been done to justify the novelty of this article.