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      A derivation of Lovász' theta via augmented lagrange duality

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      Author
      Pınar, M. Ç.
      Date
      2003
      Source 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
      Article
      Item 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 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
      Permalink
      http://hdl.handle.net/11693/24385
      Published Version (Please cite this version)
      http://dx.doi.org/10.1051/ro:2003012
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      • Department of Industrial Engineering 684
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