A sustainable fuzzy economic production quantity (SFEPQ) inventory model is formulated by introducing the concept of fuzzy differential equation (FDE) due to dynamic behavior of the production-demand system. Generalized Hukuhara (gH) differentiability proceedure is applied to solve FDE. Since the demand parameter is taken as trapezoidal type-2 fuzzy number, to get corresponding defuzzified values, first critical value (CV)-based reduction method is applied on demand function to transfer into type-1 fuzzy variable which turns to hexagonal fuzzy number in form. After that α-cut of a hexagonal fuzzy number is used to find the upper and lower value of demand. To apply the α-cut operation on FDE, we divided the interval [0,1] into two sub-intervals [0,0.5] and [0.5,1] and gH-differentiation is applied on this sub-intervals. The objective of this paper is to maximize the profit and simultaneously minimize the carbon emission cost occurring due to the process of inventory management. Finally, the non-linear objective functions are solved by using of multi-objective genetic algorithm and sensitivity analyses on various parameters are also performed in numerically and graphically.
Mathematics Subject Classification (2010). 90B05, 90B30
In this manuscript, an Economic production quantity (EPQ) model have been formulated for deteriorating items under partial trade credit policy with crisp and fuzzy demand. For fuzzy demand we take demand as a triangular fuzzy number & we consider upper & lower of this fuzzy number. Then the annual inventory cost of retailer is divided into two parts upper of annual inventory cost & lower of annual inventory cost. We use weighted sum method to convert multi objective to a single objective. Here we have to derive optimum cycle time so as to minimize the total average cost. Numerical examples are used to illustrate all results obtained in this paper. Finally the model is solved by Generalized Reduced Gradient(GRG) method and using LINGO(12) software.
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