A New Defuzzification Method for Cost Analysis of Economic Order Quantity under Cloud Pentagonal Fuzzy Demand

Abstract

The present research work explores a pentagonal dense fuzzy set (PDFS) and a novel defuzzification method for the same based on cut. The proposed concept is then applied in the field of inventory management by considering an economic order quantity (EOQ) model. To comprehend the uncertainty associated with the EOQ model, a pentagonal fuzzy number is utilized. Based on PDFS, cloud pentagonal fuzzy number (CPFN) is defined and the model is developed by considering demand as CPFN. The developed models are being tested numerically and graphically to understand the significance of the concept of CPFN. Sensitivity analysis is performed to identify the most critical parameters. A comparative analysis is made to figure out the difference between the models.