Pythagorean fuzzy EOQ model with stock- and hybrid price-dependent demand under preservation technology and advance payment

This research implements the impact of an advance payment policy on inventory management while incorporating preservation technology to mitigate product deterioration. In a real scenario, the sum of the membership and non-membership degrees of uncertain parameters is greater than one. Hence, the primary objective is to optimize cycle time, selling price and maximum profit by utilizing an advanced payment policy, hybrid price-dependent demand rate under interval-valued Pythagorean fuzzy numbers to handle imprecise parameters. Two inventory models are developed: one incorporating preservation technology and another without it. Then, the corresponding fuzzy models are obtained under interval-valued Pythagorean fuzzy environment. A novel ranking method is employed to defuzzify the models and then the defuzzified models are solved by using analytic solution method of maximization problem. The models are validated through numerical examples by assuming hypothetical data, and the results are compared across crisp, Pythagorean fuzzy, and intuitionistic fuzzy frameworks. Key findings indicate that adopting preservation technology significantly improves profitability and reduces deterioration losses. Moreover, the Pythagorean fuzzy approach proves to be more effective in capturing uncertainty compared to intuitionistic fuzzy sets. These findings suggest that businesses can enhance inventory decision-making by leveraging advanced fuzzy techniques to optimize financial and operational outcomes.