Paper Info
Title
A Multiperiod Newsvendor Problem with Partially Observed Demand
Abstract
We consider a newsvendor problem with partially observed Markovian demand. Demand is observed if it is less than the inventory. Otherwise, only the event that it is larger than or equal to the inventory is observed. These observations are used to update the demand distribution from one period to the next. The state of the resulting dynamic programming equation is the current demand distribution, which is generally infinite dimensional. We use unnormalized probabilities to convert the nonlinear state transition equation to a linear one. This helps in proving the existence of an optimal feedback ordering policy. So as to learn more about the demand, the optimal order is set to exceed the myopic optimal order. The optimal cost decreases as the demand distribution decreases in the hazard rate order. In a special case with finitely many demand values, we characterize a near-optimal solution by establishing that the value function is piecewise linear.
Year
DOI
Venue
2007
10.1287/moor.1060.0236
Math. Oper. Res.
Keywords
DocType
Volume
demand distribution,myopic optimal order,optimal feedback,demand value,Markovian demand,Partially Observed Demand,optimal order,demand distribution decrease,Multiperiod Newsvendor Problem,optimal cost decrease,hazard rate order,current demand distribution
Journal
32
Issue
ISSN
Citations 
2
0364-765X
20
PageRank 
References 
Authors
1.03
5
3
Name
Order
Citations
PageRank
Alain Bensoussan1367170.17
Metin Çakanyildirim215012.59
Suresh Sethi31215255.98