Analysis of perishable-inventory systems with censored demand data
成果类型：
Article
署名作者：
Lu, Xiangwen; Song, Jing-Sheng; Zhu, Kaijie
署名单位：
Cisco Systems Inc; Cisco USA; Duke University; Shanghai Jiao Tong University; Hong Kong University of Science & Technology
刊物名称：
OPERATIONS RESEARCH
ISSN/ISSBN：
0030-364X
DOI：
10.1287/opre.1080.0553
发表日期：
2008
页码：
1034-1038
关键词：
摘要：
We consider a multiperiod inventory system of a perishable product with unobservable lost sales. Demand distribution parameters are unknown and are updated periodically using the Bayesian approach based on the censored historical sales data. We develop an explicit expression of the first-order condition for optimality that demonstrates the key trade-off of the problem. The result generalizes partial characterizations of this trade-off in the literature. It shows that the myopic solution is a lower bound on the optimal inventory level. It also enables us to quantify the expected marginal value of information.