A derivation of Lovász' theta via augmented lagrange duality

Date

2003

Authors

Pınar, M. Ç.

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Abstract

A recently introduced dualization technique for binary linear programs with equality constraints, essentially due to Poljak et al. [13], and further developed in Lemar´echal 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 Lov´asz θ number.

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RAIRO - Operations Research

Publisher

E D P Sciences

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Keywords

Lagrange duality, Lovász theta function, Semi-definite relaxation, Stable set, Constraint theory, Linear programming, Optimization, Problem solving, Virtual reality, Lagrange duality, Lovasz theta function, Semidefinite relaxation, Stable sets, Lagrange multipliers

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Published Version (Please cite this version)

Language

English