Technical Note-Managing Nonperishable Inventories with Learning About Demand Arrival Rate Through Stockout Times

• 成果类型: Article
• 署名作者: Bensoussan, Alain; Guo, Pengfei
• 署名单位: University of Texas System; University of Texas Dallas; City University of Hong Kong; Hong Kong Polytechnic University
• 刊物名称: OPERATIONS RESEARCH
• ISSN/ISSBN: 0030-364X
• DOI: 10.1287/opre.2015.1376
• 发表日期: 2015
• 页码: 602-609
• 关键词: censored newsvendor; optimal acquisition; DEPENDENT DEMAND; management; substitution; models

摘要

We study a periodic review inventory model with a nonperishable product over an infinite planning horizon. The demand for the nonperishable product arrives according to a Poisson process. Lost sales are unobservable but the stockout times are observable. We formulate the problem as a dynamic programming model with learning on arrival rate according to stockout times and further simplify it by using unnormalized probabilities. We then compare the system performance with those under other two information scenarios where lost sales are observable or both lost sales and stockout times are unobservable. We show that the optimal inventory order-up-to level with observable stockout times is larger than the one with observable lost sales. We also show that more information improves the system performance.