Optimization of Inventory Management for Deteriorating Items with Quality-Dependent Demand under Neutrosophic Environments and Payment Delay Policies

This study presents an optimized inventory management model for deteriorating items, focusing on quality-dependent demand patterns within a generalized neutrosophic environment. Recognizing the challenges of degradation, defective products, fluctuating demand, and uncertain cost parameters, the model leverages a newly developed ranking and defuzzification approach. The study integrates a delay in payment policy, quality-linked demand, and preservation technology investment to optimize cycle time and minimize total inventory costs. The Particle Swarm Optimization (PSO) algorithm is applied to find the optimal solutions, with a sensitivity analysis exploring impacts on various inventory parameters. Results demonstrate the model's adaptability to real-world uncertainties, enhancing decision-making for sustainable inventory systems.