Article ID: | iaor20133811 |
Volume: | 77 |
Issue: | 3 |
Start Page Number: | 323 |
End Page Number: | 343 |
Publication Date: | Jun 2013 |
Journal: | Mathematical Methods of Operations Research |
Authors: | Bertsimas Dimitris, Goyal Vineet |
Keywords: | uncertainty |
In this paper, we consider adjustable robust versions of convex optimization problems with uncertain constraints and objectives and show that under fairly general assumptions, a static robust solution provides a good approximation for these adjustable robust problems. An adjustable robust optimization problem is usually intractable since it requires to compute a solution for all possible realizations of uncertain parameters, while an optimal static solution can be computed efficiently in most cases if the corresponding deterministic problem is tractable. The performance of the optimal static robust solution is related to a fundamental geometric property, namely, the