Robust solutions of Linear Programming problems contaminated with uncertain data |
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Authors: | Aharon Ben-Tal Arkadi Nemirovski |
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Institution: | (1) Faculty of Industrial Engineering and Management, Technion – Israel Institute of Technology, 32000 Haifa, Israel, e-mail: (morbt,nemirovs)@ie.technion.ac.il, IL |
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Abstract: | Optimal solutions of Linear Programming problems may become severely infeasible if the nominal data is slightly perturbed.
We demonstrate this phenomenon by studying 90 LPs from the well-known NETLIB collection. We then apply the Robust Optimization
methodology (Ben-Tal and Nemirovski 1–3]; El Ghaoui et al. 5, 6]) to produce “robust” solutions of the above LPs which are
in a sense immuned against uncertainty. Surprisingly, for the NETLIB problems these robust solutions nearly lose nothing in
optimality.
Received: July 1999 / Accepted: May 2000?Published online July 20, 2000 |
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Keywords: | |
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