The highly competitive and volatile nature of the current marketing environment makes it challenging to predict demand and other uncertain costs. To address this uncertainty, this study employs an interval-valued optimization technique. We propose an economic order quantity (EOQ) model within an interval framework, where the demand rate is represented as an interval-valued power function dependent on the green level, selling price, and time. Furthermore, the retailer’s purchasing and holding costs are treated as interval values; the purchasing cost is dependent on the green level, while the holding cost varies over time. The model also permits fully backlogged shortages, which are considered interval values. A parametric method is utilized to convert the differential equation for the inventory level from its interval form into a crisp equivalent. The resulting maximization problem is then solved using the Teaching-learning-based optimizer algorithm (TLBOA), after being converted to a crisp problem using interval order relations and the center-radius optimization approach. Finally, a numerical example is provided to illustrate and validate the proposed model, followed by a post-optimality analysis to examine the impact of various parameters on the optimal policy. (AMS classification code: 90B05, 49M37, 90C70, 90C59)
Ali et al. (Mon,) studied this question.