Mathematical Programming

, Volume 112, Issue 1, pp 125–158 | Cite as

Selected topics in robust convex optimization

  • Aharon Ben-Tal
  • Arkadi NemirovskiEmail author


Robust Optimization is a rapidly developing methodology for handling optimization problems affected by non-stochastic “uncertain-but- bounded” 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.


Optimization under uncertainty Robust optimization Convex programming Chance constraints Robust linear control 

Mathematics Subject Classification (2000)

90C34 90C05 90C20 90C22 90C15 


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Copyright information

© Springer-Verlag 2007

Authors and Affiliations

  1. 1.Faculty of Industrial Engineering and ManagementTechnion – Israel Institute of TechnologyHaifaIsrael
  2. 2.School of Industrial and Systems EngineeringGeorgia Institute of TechnologyAtlantaUSA

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