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Robust optimization: the need, the challenge, the success

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  • UserRonnie Ben-Tal (Technion, Haifa)
  • ClockThursday 26 May 2011, 15:00-16:00
  • HouseCMS, MR14.

If you have a question about this talk, please contact Dr Shadrin.

We list and illustrate by examples various sources of uncertainty associated with optimization problems. We then explain the difficulties arising when solving such uncertainty affected problems due to lack of full information on the nature of the uncertainty on one hand, and the likelihood of facing computationally intractable problems on the other hand.

Robust Optimization (RO) is a methodology that was designed from the start to meet the above challenges. We will review (part of…) the theory underlying the RO methodology and demonstrate its success in solving meaningful conic optimization problems affected by uncertainty, as well as multistage (dynamic) linear optimization problems. Examples include portfolio optimization, signal processing and supply chain management.

This talk is part of the Numerical Analysis series.

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