Optimization of Inventory Replenishment under Asymmetric Stock-Out and Inventory Holding Costs
DOI:
https://doi.org/10.23055/ijietap.2025.32.1.10035Keywords:
Inventory, perishable inventory, optimization, Metaheuristics, Genetic AlgorithmAbstract
Perishable products are an essential part of commerce. Shelf-life characteristics are usually not modeled in traditional inventory models. This study proposes an inventory replenishment model for perishable products with an asymmetric cost structure for holding and stock-out costs. The modeling phase involves the shelf-life characteristics of products. Shelf life is essential due to sustainability concerns, costs, and service levels due to perished products. In contrast to classical safety stock models, where stock-out costs increase linearly, the proposed model utilizes incrementally increased fixed costs for holding costs in a conflicting cost structure. It incorporates the shelf-life of the products, calculates the probability of perishing, and formulates accurate waste and total costs using an asymmetrical cost structure. The model is applied to a real dataset to assess the performance and compare it with the traditional approach. The performance of the proposed model is better, with a total cost reduction of 45.33%. Additionally, the model demonstrated a 17.21% increase in service level. The sensitivity analysis further underlined the robustness of the proposed model across various demand scenarios and shelf-life conditions. The main research gap addressed by this study is the lack of consideration for shelf-life characteristics and asymmetric cost structures in traditional inventory models. By integrating these factors, this research provides a more accurate and cost-effective approach to inventory management for perishable products, enhancing sustainability and service levels. This study's findings can help businesses optimize inventory strategies, reduce waste, and improve operational efficiency.
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