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Approximation and resolution of min–max and min–max regret versions of combinatorial optimization problems

Aissi, Hassene (2006), Approximation and resolution of min–max and min–max regret versions of combinatorial optimization problems, 4OR, 4, 4, p. 347-350. http://dx.doi.org/10.1007/s10288-006-0004-6

Type
Article accepté pour publication ou publié
Date
2006
Journal name
4OR
Volume
4
Number
4
Publisher
Springer
Pages
347-350
Publication identifier
Metadata
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Author(s)
Aissi, Hassene
Abstract (EN)
This is a summary of the most important results presented in the author’s PhD thesis. This thesis, written in French, was defended on November 2005 and supervised by Cristina Bazgan and Daniel Vanderpooten. A copy is available from the author upon request. This thesis deals with the complexity, approximation and resolution of the min–max and min–max versions of classical combinatorial optimization problems. In addition to these theoretical aspects, a practical application of robustness approaches to the problem of data association is considered.
Subjects / Keywords
Min–max; Min–max regret; Combinatorial optimization; Complexity; Approximation; Robustness analysis; Data association