OPTIMAL EOQ INVENTORY MODEL HAVING PRICE SENSITIVE DEMAND WITH WEIBULL DETERIORATION UNDER COMPLETE BACKLOGGED SHORTAGES IN CRISP AND FUZZY ENVIRONMENTS

This research presents an economic order quantity (EOQ) inventory model for deteriorating products with price-sensitive demand and a Weibull deterioration rate, considering complete backlogged shortages.The model is examined in both crisp and fuzzy environments to address uncertainties in inventory parameters.In the crisp setting, deterministic values are used to determine optimal inventory decisions, whereas the fuzzy approach incorporates triangular fuzzy numbers, with defuzzification performed using the graded mean integration representation (GMIR) method.The framework integrates a backlogging mechanism where the proportion of backlogged demand varies over time, aligning with real-world inventory scenarios.A mathematical optimization technique is applied to establish the optimal replenishment policy that minimizes total inventory costs.Numerical examples validate the model through Mathematica 13.0.1 software, and a sensitivity analysis explores the influence of key parameters on optimal solutions.The managerial insights derived from this study provide valuable strategies for retailers managing perishable goods and operating in price-sensitive markets.