- Library Home /
- Search Collections /
- Open Collections /
- Browse Collections /
- BIRS Workshop Lecture Videos /
- On the Heavy-Tail Behavior of the Distributionally...
Open Collections
BIRS Workshop Lecture Videos
BIRS Workshop Lecture Videos
On the Heavy-Tail Behavior of the Distributionally Robust Newsvendor Model with Moment Constraints Natarajan, Karthik
Description
Since the seminal work of Scarf (1958) on the newsvendor problem with ambiguity in the demand distribution, there has been a growing interest in the study of the distributionally robust newsvendor problem. Scarf's solution is criticized at times for being overly conservative since the worst-case distribution is discrete with a few support points. A simple observation however indicates that the optimal order quantity in this two moment model is also optimal for a censored student-t distribution with infinite variance for all possible values of the critical ratio. In this paper, we generalize this ``heavy tail optimality" property of the distributionally robust newsvendor to the case when information on the first and the nth moment is known for any rational number n > 1. This is joint work with Anulekha Dhara (University of Michigan) and Bikramjit Das (SUTD).
Item Metadata
| Title |
On the Heavy-Tail Behavior of the Distributionally Robust Newsvendor Model with Moment Constraints
|
| Creator | |
| Publisher |
Banff International Research Station for Mathematical Innovation and Discovery
|
| Date Issued |
2018-03-09T11:14
|
| Description |
Since the seminal work of Scarf (1958) on the newsvendor problem with ambiguity in the demand distribution, there has been a growing interest in the study of the distributionally robust newsvendor problem. Scarf's solution is criticized at times for being overly conservative since the worst-case distribution is discrete with a few support points. A simple observation however indicates that the optimal order quantity in this two moment model is also optimal for a censored student-t distribution with infinite variance for all possible values of the critical ratio. In this paper, we generalize this ``heavy tail optimality" property of the distributionally robust newsvendor to the case when information on the first and the nth moment is known for any rational number n > 1. This is joint work with Anulekha Dhara (University of Michigan) and Bikramjit Das (SUTD).
|
| Extent |
30 minutes
|
| Subject | |
| Type | |
| File Format |
video/mp4
|
| Language |
eng
|
| Notes |
Author affiliation: Singapore University of Technology and Design
|
| Series | |
| Date Available |
2018-09-05
|
| Provider |
Vancouver : University of British Columbia Library
|
| Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
|
| DOI |
10.14288/1.0371933
|
| URI | |
| Affiliation | |
| Peer Review Status |
Unreviewed
|
| Scholarly Level |
Faculty
|
| Rights URI | |
| Aggregated Source Repository |
DSpace
|
Item Media
Item Citations and Data
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International