Document Type : Article
Authors
1
Department of Industrial Engineering, Faculty of Engineering, Ardakan University, Ardakan, Iran
2
Industrial Engineering Department, Faculty of Engineering, Ardakan University, Ardakan, Iran
3
Department, Faculty of Engineering, Ardakan University, Ardakan, Iran
10.24200/j65.2025.67361.2443
Abstract
With the rapid advancement of technology and the increasing consumption of perishable or obsolete-prone products such as electronic devices, pharmaceuticals, and medical equipment, inventory control for these items has become more critical than ever. Proper inventory management of such items not only prevents excessive costs but also significantly reduces waste and environmental hazards. This study presents an inventory control model for perishable items that simultaneously incorporates three key factors: all-units quantity discount, the probability of sudden obsolescence, and holding cost dependent on purchase cost. In the proposed model, suppliers offer discounts based on order quantity thresholds, and the holding cost is defined as a function of the item's purchase cost. The model is designed to assist decision-makers in balancing order quantity, financial costs, and obsolescence risks under real-world conditions.
The main objective is to determine the optimal economic order quantity (EOQ) that minimizes the total inventory cost while avoiding stockouts and accounting for the risk of obsolescence. To achieve this, a mathematical formulation of purchasing, ordering, holding, and obsolescence costs was developed. The convexity of the objective function was proven using first- and second-order derivatives, and graphical analysis. A numerical example using real-world data was provided to evaluate model performance, and a sensitivity analysis was conducted to examine the impact of key parameters. In addition, the model’s stability was analyzed under different economic scenarios.
The results show that increasing ordering costs leads to higher order quantities, which in turn reduces purchasing costs due to quantity discounts. Moreover, increasing the purchase elasticity coefficient reduces the order quantity, resulting in lower total inventory costs. On the other hand, increasing the holding cost coefficient or obsolescence-related costs can significantly raise total system costs. Overall, the model enables a better understanding of how price-dependent costs and obsolescence risks interact, helping organizations optimize their inventory strategies. The proposed approach can serve as an effective tool for inventory decision-making in environments dealing with time-sensitive or rapidly outdated items.
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