Recent Advances in Robust Optimization

Aharon Ben-Tal ()
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Aharon Ben-Tal: Technion

A chapter in Operations Research Proceedings 2006, 2007, pp 69-69 from Springer

Abstract: Abstract We will briefly survey the state of the art of the Robust Optimization (RO) methodology for solving convex conic optimization problems, both static and dynamic (multi-stage) emphasizing issues of computational tractability, and probabilistic guarantees satisfied by the optimal robust solution. We then introduce a recent extension of the methodology in which the solution is required to exhibit a controlled deterioration in the performance for uncertain data outside the nominal uncertainty set. Finally we discuss uncertainly affected linear control systems and introduce a novel reparameterization scheme that converts the, otherwise nonconvex, control problem into a convex programming one.

Date: 2007
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Persistent link: https://EconPapers.repec.org/RePEc:spr:oprchp:978-3-540-69995-8_10

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DOI: 10.1007/978-3-540-69995-8_10

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