Research Project: Kısa Ömürlü Dayanıksız Ürünler İçin Koordineli Envanter ve Fiyat Yönetimi
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Contributors
Funders
ID
TB.00087
Authors
Kaya, Onur
Faculty Member
Publications
Inventory control and pricing for perishable products under age and price dependent stochastic demand
(Springer, 2018) Ghahroodi, Sajjad Rahimi; Kaya, Onur; Department of Industrial Engineering; No; College of Engineering
Perishable products have a short lifetime and cause a high amount of wastage when managed ineffectively, due to their deterioration over time. We consider coordinated inventory and pricing decisions for perishable products in a periodically-reviewed inventory system with an age and price dependent random demand. We consider the products with a fixed shelf lifetime and use dynamic programming to model this system. We prove certain structural characteristics of the optimal solution and also analyze the effect of different parameters on the optimal solution through numerical experiments. In addition, we analyze simple-to-implement inventory control policies, namely quantity-based and age-based policies, and investigate their effectiveness.
Coordinated pricing and inventory decisions for perishable products
(Springer, 2017) Polat, Aylin Lelizar; Kaya, Onur; Department of Industrial Engineering; No; College of Engineering
We investigate the problem of jointly determining the optimal pricing and inventory replenishment strategy for a deterministic perishable inventory system in which demand is time and price dependent. The inventory is also assumed to decay at a certain rate. The seller has the opportunity to adjust prices for a discrete number of times at a certain cost during the sales season to influence demand and to improve revenues. We develop a mathematical model to find the optimal times to change the prices, the optimal prices and the optimal order quantity. We present analytical results to find the optimal prices when the times of price changes are given and design heuristic algorithms to determine the optimal times to change the prices. We analyze the efficiency of multiple pricing strategy by comparing the profits obtained by single pricing case and also analyze the effect of different parameters on the optimal solution through numerical experiments.
