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A Robust Robust Optimization Result

Martina Gancarova(martina.gancarova***at***gmail.com)
Michael Todd(mjt7***at***cornell.edu)

Abstract: We study the loss in objective value when an inaccurate objective is optimized instead of the true one, and show that ``on average'' this loss is very small, for an arbitrary compact feasible region.

Keywords:

Category 1: Robust Optimization

Citation: Technical Report 1479, School of Operations Research and Information Engineering, Cornell University, Ithaca, NY 14853, April 2011

Download: [PDF]

Entry Submitted: 04/29/2011
Entry Accepted: 04/29/2011
Entry Last Modified: 04/29/2011

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