A derivation of Lovász' theta via augmented lagrange duality
Author
Pınar, M. Ç.
Date
2003Source Title
RAIRO - Operations Research
Print ISSN
0399-0559
Electronic ISSN
1290-3868
Publisher
E D P Sciences
Volume
37
Issue
1
Pages
17 - 27
Language
English
Type
ArticleItem Usage Stats
133
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77
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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.
Keywords
Lagrange dualityLovász 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