Mathematical Programming

, Volume 88, Issue 3, pp 411–424

Robust solutions of Linear Programming problems contaminated with uncertain data

  • Aharon Ben-Tal
  • Arkadi Nemirovski

DOI: 10.1007/PL00011380

Cite this article as:
Ben-Tal, A. & Nemirovski, A. Math. Program. (2000) 88: 411. doi:10.1007/PL00011380

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.

Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Aharon Ben-Tal
    • 1
  • Arkadi Nemirovski
    • 1
  1. 1.Faculty of Industrial Engineering and Management, Technion – Israel Institute of Technology, 32000 Haifa, Israel, e-mail: (morbt,nemirovs)@ie.technion.ac.ilIL

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