EPQ Inventory Models under mλ-Measure

This chapter considers an EPQ model with and without shortages under linear combination of Possibility measure and Necessity measure. Based on the possibility measure and necessity measure, m? -measure is introduced and some important properties are discussed. To capture the real life situation, various EPQ model parameters for instance, demand, setup cost, holding cost and backorder cost are characterized as Trapezoidal Fuzzy Number. Two fuzzy chance-constrained programming models are constructed under m?-measure. The objective is to determine optimistic and pessimistic values of the fuzzy objective function with some predefined degree of m?-measure. Using fuzzy arithmetical operations under Function Principle, the fuzzy problem is first transferred to an equivalent crisp problem. An analytical approach is developed to resolve the reduced models. To investigate the characteristics of the proposed model and to obtain the optimal decision under different situations, numerical illustrations are presented along with a sensitivity analysis.