A derivation of Lovász' theta via augmented Lagrange duality
RAIRO - Operations Research - Recherche Opérationnelle, Tome 37 (2003) no. 1, pp. 17-27.

A recently introduced dualization technique for binary linear programs with equality constraints, essentially due to Poljak et al. [13], and further developed in Lemaréchal and Oustry [9], leads to simple alternative derivations of well-known, important relaxations to two well-known problems of discrete optimization: the maximum stable set problem and the maximum vertex cover problem. The resulting relaxation is easily transformed to the well-known Lovász $\theta$ number.

DOI : https://doi.org/10.1051/ro:2003012
Classification : 90C27,  90C27,  90C35
Mots clés : Lagrange duality, stable set, Lovász theta function, semidefinite relaxation
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author = {Pinar, Mustapha \c{C}.},
title = {A derivation of {Lov\'asz'} theta via augmented {Lagrange} duality},
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Pinar, Mustapha Ç. A derivation of Lovász' theta via augmented Lagrange duality. RAIRO - Operations Research - Recherche Opérationnelle, Tome 37 (2003) no. 1, pp. 17-27. doi : 10.1051/ro:2003012. http://www.numdam.org/articles/10.1051/ro:2003012/

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