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Bi-objective matchings with the triangle inequality

Gourvès, Laurent; Monnot, Jérôme; Pascual, Fanny; Vanderpooten, Daniel (2017), Bi-objective matchings with the triangle inequality, Theoretical Computer Science, 670, p. 1-10. 10.1016/j.tcs.2017.01.012

Type
Article accepté pour publication ou publié
Date
2017
Journal name
Theoretical Computer Science
Volume
670
Publisher
Elsevier
Pages
1-10
Publication identifier
10.1016/j.tcs.2017.01.012
Metadata
Show full item record
Author(s)
Gourvès, Laurent
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Monnot, Jérôme cc
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Pascual, Fanny

Vanderpooten, Daniel
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Abstract (EN)
This article deals with a bi-objective matching problem. The input is a complete graph and two values on each edge (a weight and a length) which satisfy the triangle inequality. It is unlikely that every instance admits a matching with maximum weight and maximum length at the same time. Therefore, we look for a compromise solution, i.e. a matching that simultaneously approximates the best weight and the best length. For which approximation ratio ρ can we guarantee that any instance admits a ρ-approximate matching? We propose a general method which relies on the existence of an approximate matching in any graph of small size. An algorithm for computing a 1/3-approximate matching in any instance is provided. The algorithm uses an analytical result stating that every instance on at most 6 nodes must admit a 1/2-approximate matching. We extend our analysis with a computer-aided approach for larger graphs, indicating that the general method may produce a 2/5-approximate matching. We conjecture that a 1/2-approximate matching exists in any bi-objective instance satisfying the triangle inequality.
Subjects / Keywords
Bi-objective optimization; Approximation algorithm; Matching

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