Seminar by Prof. Erick Delage, HEC Montréal
Event details
| Date | 22.07.2015 |
| Hour | 12:00 › 13:30 |
| Speaker | Prof. Erick Delage, HEC Montréal |
| Location | |
| Category | Conferences - Seminars |
"Linearized Robust Counterparts of Two-Stage Distribution Problems"
Abstract
We study two-stage distribution problems wherein some (explicit or implicit) decisions are implemented only once the demand for products has been revealed. Since the robust optimization formulation of this problem is computationally intractable we propose a conservative tractable approximation scheme for this problem based on linearizing the cross terms that appears due to the recourse problem. We relate this new scheme to methods that are based on exploiting affine decision rules. Furthermore, we show that our proposed method can be exploited to provide exact solutions in a family of robust multi-item newsvendor problem. Using a robust facility location problem, we also show how our proposed method can be used to derive conservative approximations that are tighter than existing tractable methods. This is joint work with my PhD student Amir Ardestani-Jaafari.
Bio
Erick Delage completed is Ph.D. at Stanford University in 2009, is currently associate professor in the Department of Decision Sciences at HEC Montréal and was recently appointed as chairholder of Canada Research Chair in Decision Making under Uncertainty. He is currently visiting CDM until August 31st 2015.
Abstract
We study two-stage distribution problems wherein some (explicit or implicit) decisions are implemented only once the demand for products has been revealed. Since the robust optimization formulation of this problem is computationally intractable we propose a conservative tractable approximation scheme for this problem based on linearizing the cross terms that appears due to the recourse problem. We relate this new scheme to methods that are based on exploiting affine decision rules. Furthermore, we show that our proposed method can be exploited to provide exact solutions in a family of robust multi-item newsvendor problem. Using a robust facility location problem, we also show how our proposed method can be used to derive conservative approximations that are tighter than existing tractable methods. This is joint work with my PhD student Amir Ardestani-Jaafari.
Bio
Erick Delage completed is Ph.D. at Stanford University in 2009, is currently associate professor in the Department of Decision Sciences at HEC Montréal and was recently appointed as chairholder of Canada Research Chair in Decision Making under Uncertainty. He is currently visiting CDM until August 31st 2015.
Practical information
- General public
- Free