Robust evaluations for duals of non-negative linear programs with box-constrained uncertainties

Authors

  • Ilya Ioslovich Technion
  • Per-Olof Gutman Faculty of Civil and Environmental Engineering, Technion

Keywords:

Large scale linear programming, redundancy, presolving, evaluation of dual variables, robust reduction

Abstract

Non-negative linear programs with box-constrained uncertainties for all input data and box-constrained variables are considered. The knowledge of upper bounds for dual variables is a useful information e.g. for presolving analysis aimed at the determination of redundant primal variables. The upper bounds of the duals are found by solving a set of special continuous knapsack problems, one for each row constraint.

Author Biographies

Ilya Ioslovich, Technion

Visiting professor, Faculty of Civil and Environmental Engineering, Technion

Per-Olof Gutman, Faculty of Civil and Environmental Engineering, Technion

Professor, Faculty of Civil and Environmental Engineering, Technion

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Published

2008-03-25

How to Cite

Ioslovich, I., & Gutman, P.-O. (2008). Robust evaluations for duals of non-negative linear programs with box-constrained uncertainties. Algorithmic Operations Research, 3(1). Retrieved from https://journals.lib.unb.ca/index.php/AOR/article/view/4667

Issue

Vol. 3 No. 1 (2008)

Section

Articles

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