## Selected topics in robust convex optimization (2007)

### Cached

### Download Links

- [users.ece.utexas.edu]
- [www2.isye.gatech.edu]
- [www.optimization-online.org]
- [www2.isye.gatech.edu]
- DBLP

### Other Repositories/Bibliography

Venue: | Math. Prog. B, this issue |

Citations: | 14 - 2 self |

### BibTeX

@INPROCEEDINGS{Ben-tal07selectedtopics,

author = {Aharon Ben-tal and Arkadi Nemirovski},

title = {Selected topics in robust convex optimization},

booktitle = {Math. Prog. B, this issue},

year = {2007}

}

### OpenURL

### Abstract

Abstract Robust Optimization is a rapidly developing methodology for handling optimization problems affected by non-stochastic “uncertain-butbounded” data perturbations. In this paper, we overview several selected topics in this popular area, specifically, (1) recent extensions of the basic concept of robust counterpart of an optimization problem with uncertain data, (2) tractability of robust counterparts, (3) links between RO and traditional chance constrained settings of problems with stochastic data, and (4) a novel generic application of the RO methodology in Robust Linear Control. Keywords optimization under uncertainty · robust optimization · convex programming · chance constraints · robust linear control