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<p>The proposed study investigates optimal pricing and replenishment strategies for perishable food items, such as packed foods, sauces, and dairy products. These items are susceptible to deterioration, which complicates the challenge of enhancing per-unit profit for suppliers and retailers, particularly when customer preferences shift. This challenge arises when the initial demand for products becomes fixed, but customer preferences change due to external factors like taste, color, and product attributes. The situation becomes even more complicated when these products are prone to spoilage. Consequently, this study aims to assist inventory managers in making informed decisions about when and how much to order—an ongoing challenge in inventory management. A mathematical model is presented to determine optimal replenishment timing, selling prices, and inventory cycles, accompanied by a detailed comparative analysis of various market scenarios. The results indicate that retailers can achieve a profit of $2.99 per unit through the strategies proposed in this study. These findings significantly enhance inventory systems by improving ordering policies. Additionally, a sensitivity analysis is conducted to help mitigate unexpected risks associated with changes in demand, customer preferences, and pricing.</p>

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Optimal replenishment policy for deteriorating items with linear demand and Weibull deterioration: adapting to changing customer preferences

  • 期刊论文

  • 发表日期：

    2025年11月20日

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  • Jitendra Kaushik

摘要

The proposed study investigates optimal pricing and replenishment strategies for perishable food items, such as packed foods, sauces, and dairy products. These items are susceptible to deterioration, which complicates the challenge of enhancing per-unit profit for suppliers and retailers, particularly when customer preferences shift. This challenge arises when the initial demand for products becomes fixed, but customer preferences change due to external factors like taste, color, and product attributes. The situation becomes even more complicated when these products are prone to spoilage. Consequently, this study aims to assist inventory managers in making informed decisions about when and how much to order—an ongoing challenge in inventory management. A mathematical model is presented to determine optimal replenishment timing, selling prices, and inventory cycles, accompanied by a detailed comparative analysis of various market scenarios. The results indicate that retailers can achieve a profit of $2.99 per unit through the strategies proposed in this study. These findings significantly enhance inventory systems by improving ordering policies. Additionally, a sensitivity analysis is conducted to help mitigate unexpected risks associated with changes in demand, customer preferences, and pricing.