Displaying similar documents to “On the robustness of optimal solutions for combinatorial optimization problems”

On the complexity of determining tolerances for ε-optimal solutions to min-max combinatorial optimization problems

Diptesh Ghosh, Gerard Sierksma (2003)

Applicationes Mathematicae

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This paper studies the complexity of sensitivity analysis for optimal and ε-optimal solutions to general 0-1 combinatorial optimization problems with min-max objectives. Van Hoesel and Wagelmans [9] have studied the complexity of sensitivity analysis of optimal and ε-optimal solutions to min-sum problems, and Ramaswamy et al. [17] the complexity of sensitivity analysis of optimal solutions to min-max problems. We show that under some mild assumptions the sensitivity analysis of ε-optimal...

Tractable algorithms for chance-constrained combinatorial problems

Olivier Klopfenstein (2009)

RAIRO - Operations Research

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This paper aims at proposing tractable algorithms to find effectively good solutions to large size chance-constrained combinatorial problems. A new robust model is introduced to deal with uncertainty in mixed-integer linear problems. It is shown to be strongly related to chance-constrained programming when considering pure 0–1 problems. Furthermore, its tractability is highlighted. Then, an optimization algorithm is designed to provide possibly good solutions to chance-constrained...

Robust real-time optimization for the linear oil blending

Stefan Janaqi, Jorge Aguilera, Meriam Chèbre (2013)

RAIRO - Operations Research - Recherche Opérationnelle

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In this paper we present a robust real-time optimization method for the online linear oil blending process. The blending process consists in determining the optimal mix of components so that the final product satisfies a set of specifications. We examine different sources of uncertainty inherent to the blending process and show how to address this uncertainty applying the Robust Optimization techniques. The polytopal structure of our problem permits a simplified robust approach. Our...

Deterministic global optimization using interval constraint propagation techniques

Frederic Messine (2010)

RAIRO - Operations Research

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The purpose of this article is to show the great interest of the use of propagation (or pruning) techniques, inside classical interval Branch-and-Bound algorithms. Therefore, a propagation technique based on the construction of the calculus tree is entirely explained and some properties are presented without the need of any formalism (excepted interval analysis). This approach is then validated on a real example: the optimal design of an electrical rotating machine.