Optimizing of Multi-objective Inventory Model by Different Fuzzy Techniques

In this study, multi-objective inventory model of deteriorating and perishable items is developed under space and budget constraints. Demand is stock dependent and power function of time. This model is completely a new model in the sense that the model is applied to those items whose deterioration rate is maximum. Shortages are allowed in each cycle. The main aim of this paper is to find different time points for each cycle where shortage occurs and inventory depletes respectively so that both total cost and shortage cost can be minimized simultaneously. The model is developed in both crisp and fuzzy environment. In fuzzy environment, the objectives are considered as fuzzy constraints. For this the decision maker needs to establish an aspiration level for the objective functions which he wants to achieve as far as possible. This paper aims to use fuzzy non-linear programming (FNLP) and intuitionistic fuzzy optimization (IFO) techniques for the multi-objective inventory model. Comparison is based on different optimization techniques in different environment using numerical examples. Graph of the objective functions are provided. System diagram of the model and algorithm for solving the model are provided. Also, sensitivity analysis is made using different parameters of the model.

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“…Solution of model( 10) using input data of Table 1 taken from Mishra and Umap [23] in fuzzy environment is as follows.…”

Section: Results Of the Monlp Problem In Fuzzy Environmentmentioning

confidence: 99%