Optimizing the Inventory System in Fuzzy Environment Using Ramp Type Demand Function

• Dinkar Dubey

  Jec

  Author

• Han Jian Ting

  Author

• Sahil Patel

  Author

In unpredictable times, inventory control is essential to cutting expenses and increasing productivity. Conventional Economic Order Quantity (EOQ) models may not account for real-world variability since they optimize inventory using deterministic assumptions. For deteriorating items with ramptype demand, this paper creates both a crisp and a fuzzy EOQ model. By representing holding, shortage, and deterioration costs as trapezoidal fuzzy numbers, the fuzzy model makes it possible to handle uncertainty and imprecise information more effectively. The effectiveness of the fuzzy model in lowering inventory costs is demonstrated by comparative numerical analysis, which shows that it produces a lower total cost than the crisp model. The study offers a framework for future extensions to other uncertain parameters and emphasizes the advantages of integrating fuzzy logic into inventory management.

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• 2025-10-15 (2)
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