Publication Date: 2022/04/05
Abstract: This work considers inventory systems that models uncertainties in demand and various fuzzy inventory cost parameters. However, in many cases where there is little or no historical data available to decision makers due to recent changes in the supply chain environment, probability distribution may simply not be available, or may not easily or accurately be estimated. In this paper we consider fuzzy inventory model with three fuzzy parameters and shortages not permitted. Fuzziness in this model occurs in the demand of product, holding costs and ordering costs. The inventory lead time is assumed to be zero. To obtain the total fuzzy costs, the three fuzzy parameters have been represented using Pentagonal fuzzy numbers (PFN). The economic ordered quantity (EOQ) and total inventory costs has also been computed by defuzzification of the fuzzy economic ordered quantity and total fuzzy costs using the graded mean integration approach. A numerical example is provided to compare our model with the four fuzzy set parameters with those with crisp parameters.
Keywords: Demand, Defuzzification, Inventory cost, pentagonal fuzzy numbers, Graded mean integration representation method.
DOI: https://doi.org/10.5281/zenodo.6414944
PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT22MAR559_(3).pdf
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