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Neutrosophic Cost Pattern of Inventory System with Novel Demand Incorporating Deterioration and Discount on Defective

G Durga Bhavani1, Fasika Bete Georgise2, G S Mahapatra1

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This study introduces an inventory system to minimize costs for retailers receiving defective items. It addresses uncertainty in costs, demand, and item deterioration using a neutrosophic environment and optimization.

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Area of Science:

  • Operations Research
  • Supply Chain Management
  • Inventory Management

Background:

  • Retailers frequently encounter defective items from suppliers, impacting costs and efficiency.
  • Existing inventory models often struggle to account for uncertainties in costs, demand, and product deterioration.

Purpose of the Study:

  • To develop an inventory system that minimizes total costs for retailers receiving defective items.
  • To incorporate uncertainty in inventory costs, demand, and item deterioration into an inventory model.
  • To prioritize products with maximum life and consider payment delays and interest charges.

Main Methods:

  • Utilizing a neutrosophic environment to handle uncertainty in cost patterns.
  • Modeling demand as a function of reliability and time's power pattern.
  • Employing a particle swarm optimization algorithm for model investigation.

Main Results:

  • The proposed inventory system effectively minimizes total inventory costs under uncertain conditions.
  • The model successfully integrates demand, deterioration, and cost uncertainties.
  • Sensitivity analysis validates the robustness of the proposed model.

Conclusions:

  • The developed inventory model provides a robust framework for managing defective items and associated uncertainties.
  • Neutrosophic logic and optimization algorithms are effective tools for complex inventory problems.
  • The system offers practical benefits for retailers aiming to reduce costs and improve efficiency.