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Selected Topics in Robust Convex Optimization

Aharon Ben-Tal (abental***at***ie.technion.ac.il)
Arkadi Nemirovski (nemirovs***at***isye.gatech.edu)

Abstract: 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 {\sl 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, chance constraints, robust linear control

Category 1: Robust Optimization

Category 2: Stochastic Programming

Category 3: Applications -- Science and Engineering (Control Applications )

Citation: The paper underlies the plenary lecture given by the second author at ISMP 2006 and will be published in the ISMP 2006 Special Issue of Mathematical Programming Series B

Download: [PDF]

Entry Submitted: 09/12/2006
Entry Accepted: 09/12/2006
Entry Last Modified: 09/12/2006

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