• The Journal of Fisheries Business Administration
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• v.25 no.2
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• pp.103-114
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• 1994

We consider the continous, deterministic, infinite horiton, perishable item inventory, within the setting of a retail sector, in which the price for an item is dependent on the lifetime of inventory. Replenishment cost is kept constant but the carrying cost per units is allowed to vary according to product lifetime. Tro possibilities of variation are considered : (1) Product lifetime is longer than cycletime and (2) Product lifetime is shorter than cycletime. We find the optimal policies and decision rules for perishable product.

• Journal of applied mathematics & informatics
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• v.5 no.1
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• pp.253-261
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• 1998

(s,S) inventrory system of a perishable item with positive lead times and finite backlogs under N-policy Under this policy as and when the inventory level drops to s-N during a lead time local purchase is made. Three models are con-sidered. The limiting distribution on the inventory level is obtained and an associated cost analysis is made. Results ae numerically illustrated.

• Journal of applied mathematics & informatics
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• v.26 no.3_4
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• pp.615-625
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• 2008

A single item order level inventory model for perishable products is considered in which a constant fraction of on hand inventory spoils per unit time. Demand linearly depends on time. The fluctuation of demand is taken into account to determine minimum total cost of the system. Both discrete and continuous fluctuations are considered. The model is developed and solved analytically for infinite time horizon. A numerical example is presented for finite time horizon. Sensitivity analysis of the model is carried out.

• Journal of the Korean Operations Research and Management Science Society
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• v.33 no.2
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• pp.137-151
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• 2008

This paper deals with two shops dealing with single perishable product the fresh items are sold at a list price in the primary shop and the unsold items that have reached a certain allowed age are transferred to the secondary shop to be sold at a discounted price. It is assumed that the demand rates in two shops are Independent each other and can be expressed as a function of inventory level and price. With the objective of maximizing the profit under a Last-In-first-Out. (LIFO) issuing policy, we develop mathematical models for the following two cases : (1) opening primary shop only and (2) opening both primary shop and secondary shop. There are three decision variables, i.e., the reduced price in the secondary shop, the allowed age at the primary shop, and the order quantities at the primary shop. A solution procedure is developed based on tabu search and its validity is illustrated through a comparative study.

• Journal of Information Technology Applications and Management
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• v.30 no.3
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• pp.1-13
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• 2023

Demand forecasting is a crucial task for an online retail where has to manage daily fresh foods effectively. Failing in forecasting results loss of profitability because of incompetent inventory management. This study investigated the optimal performance of different forecasting models for a very short shelf-life product. Demand data of 13 perishable items with aging of 210 days were used for analysis. Our comparison results of four methods: Trivial Identity, Seasonal Naïve, Feed-Forward and Autoregressive Recurrent Neural Networks (DeepAR) reveals that DeepAR outperforms with the lowest MAPE. This study also suggests the managerial implications by employing coefficient of variation (CV) as demand variation indicators. Three classes: Low, Medium and High variation are introduced for classify 13 products into groups. Our analysis found that DeepAR is suitable for medium and high variations, while the low group can use any methods. With this approach, the case can gain benefit of better fill-rate performance.

• The Journal of Fisheries Business Administration
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• v.30 no.2
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• pp.25-37
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• 1999

Some multi echelon inventory systems carry perishable products. The value of these product reduces as the period of time they spend in the system. In this paper We derive the necessary condition to determine optimal quantity, service level for a perishable product. The systems considered consist of two echelons and carry single item. To determine the optimal order quantity, the demand is assumed to be constant, the holding costs may be different in the echelons, and it allows no shortages. I assumed the price of product decreases by negative exponential function. To determine service level, following assumptions used in the model ㆍlead time is constant. ㆍdemand is normal distribution. ㆍthe product starts to perish at the second echelon. Service level is computed for different levels of lead times and for different variance of demands and for different price functions. The experimental results indicate that the service level in cost is a function of service level in demand and perishability of product. Results of the models exhibit that perishability and the age of the product are critical to determine the lot sizing and service level.