hal-00717212, version 4
Improved semidefinite branch-and-bound algorithm for k-cluster
Résumé : This paper presents a method to solve k-cluster problems by intersecting semidefinite and polyhedral relaxations. We use a generic branch-and-bound method featuring an improved semidefinite bounding procedure. Extensive numerical experiments show that our algorithm outperforms the best known methods in both time and ability to solve large instances. For the first time, numerical results are reported for k-cluster problems on unstructured graphs with 140 and 160 vertices.
- a – INRIA
- b – CNRS
- 1 :
- INRIA – Laboratoire Jean Kuntzmann
- 2 :
- CNRS : UMR5224 – Université Joseph Fourier - Grenoble I – Université Pierre-Mendès-France - Grenoble II – Institut Polytechnique de Grenoble - Grenoble Institute of Technology
- 3 :
- CNRS : UMR7030 – Université Paris XIII - Paris Nord
- Domaine : Mathématiques/Optimisation et contrôle
Informatique/Mathématique discrète
Informatique/Recherche opérationnelle - Mots-clés : combinatorial optimization – semidefinite programming – triangle inequalities – k-cluster problem – k-densest subgraph problem
- Versions disponibles : v1 (12-07-2012) v2 (13-07-2012) v3 (13-07-2012) v4 (14-07-2012)
- hal-00717212, version 4
- http://hal.inria.fr/hal-00717212
- oai:hal.inria.fr:hal-00717212
- Contributeur :
- Soumis le : Vendredi 13 Juillet 2012, 16:52:01
- Dernière modification le : Samedi 14 Juillet 2012, 12:56:20





Documents associés
Exporter