An Inventory Ordering Model with Different Defuzzification Techniques Under Inflation

Abstract

The various cost associated with the inventory model are not fixed in nature. These vary as per the current market conditions. A crisp inventory problem framework includes these parameters with fixed value. Fuzzy logics incorporate in it the uncertainties that are prevailing in the market for these parameters. Thus a fuzzy inventory problem model presents a more accurate measure for the optimality of the inventory problem. In the current inventory problem discussed under an inflationary backdrop, pentagonal and hexagonal fuzzy numbers are used to define the inexactness in the cost parameters. The defuzzification of the fuzzified total cost is done using signed distance method. A comparative study is done for the final cost of the crisp inventory problem with the defuzzified cost value of the problem under pentagonal and hexagonal number system. Numerical solution validate the result. Logical insights developed in the problem are analyzed with the numericals done.