Application of freshness preservation technologies in case of perishable inventory management can play a vital role in mitigating the losses that occur due to deterioration of perishable inventory, typical perishable inventory includes Agri-fresh products like fresh fruits, fresh meat, fresh vegetables, seafood and packed foods. In case of perishable inventory price as well as freshness both decide the demand, so supplying a fresh product at a competitive price creates more customer satisfaction and makes a firm profitable. This paper develops two warehouse dispatching policies, first in, first out (FIFO) and last in, first out (LIFO) for perishable items taking deterioration into account. Demand varies as a function of price and freshness keeping effort. As the price increases and freshness keeping efforts decreases, demand decreases, and vice versa. Stockout is allowed, and during the stockout period as the waiting time increases backlogging rate decreases exponentially. Inflation is considered while calculating different costs. The objective of this paper is to determine the optimum price per unit item and lot size to maximize the profit. The sensitivity of the models is examined through the design of experiment. The present models are applicable for perishable items that start losing their quality immediately after arriving into the system.

在易腐库存管理中应用保鲜技术可以在减轻因易腐库存恶化而造成的损失方面发挥至关重要的作用，典型的易腐库存包括新鲜水果，新鲜肉类，新鲜蔬菜，海鲜和包装农产品等农产品食物。如果库存价格易变坏以及新鲜度都决定需求，那么以具有竞争力的价格提供新鲜产品可提高客户满意度并确保公司盈利。本文针对易腐物品制定了两种仓库调度策略，即先进先出（FIFO）和后进先出（LIFO），同时考虑了变质问题。需求随价格和保鲜力的变化而变化。随着价格上涨和保持新鲜感的努力减少，需求减少，反之亦然。允许缺货，并且在缺货期间，随着等待时间的增加，积压率呈指数下降。在计算不同成本时会考虑通货膨胀。本文的目的是确定每件商品的最佳价格和批量，以使利润最大化。通过实验设计检查模型的敏感性。本模型适用于易腐物品，这些物品在进入系统后立即开始失去其质量。通过实验设计检查模型的敏感性。本模型适用于易腐物品，这些物品在进入系统后立即开始失去其质量。通过实验设计检查模型的敏感性。本模型适用于易腐物品，这些物品在进入系统后立即开始失去其质量。