Volume 25 , Issue 4 , PP: 472-483, 2025 | Cite this article as | XML | Html | PDF | Full Length Article
Kalaiarasi K. 1 , Nasreen Kausar 2 , Said Broumi 3 , Tonguc Cagin 4
Doi: https://doi.org/10.54216/IJNS.250440
The fuzzy stock administration demonstrates displayed in this work employments neutrosophic set hypothesis, pentagonal fuzzy numbers, and the Graded mean Integration Representation (GMIR) strategy for defuzzification. Request rates, arrange amounts, utilization rates, holding costs, setup costs, and deficiency costs are all spoken to as fuzzy parameters within the demonstrate to account for the inborn instability and vacillation. To reduce by and large costs, the whole cost work is calculated, taking setup, holding, and shortage costs into consideration. In arrange to speak to the combined impacts of a few fetched components, the overall taken a toll work is rearranged and the ideal arrange amount is built up beneath fuzzy conditions utilizing pentagonal fuzzy parameters. The demonstrate is assessed beneath different degrees of instability through a case-based investigation, advertising an exhaustive system for making choices on stock administration in equivocal and dubious circumstances. The results appear how versatile and capable the show is for improving fetched advancement and stock control.
Fuzzy Inventory Management , Pentagonal Fuzzy Numbers , Neutrosophic Set Theory , Graded Mean Integration Representation (GMIR) , Defuzzification , Total Cost Function , Optimization , Uncertainty , Inventory Control , Cost Minimization , Fuzzy Decision-Making , Supply Chain Management
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