Journal of Combinatorial Optimization

, Volume 29, Issue 2, pp 433–450 | Cite as

A tolerance-based heuristic approach for the weighted independent set problem

  • B. I. Goldengorin
  • D. S. MalyshevEmail author
  • P. M. Pardalos
  • V. A. Zamaraev


The notion of a tolerance is a helpful tool for designing approximation and exact algorithms for solving combinatorial optimization problems. In this paper we suggest a tolerance-based polynomial heuristic algorithm for the weighted independent set problem. Several computational experiments show that our heuristics works very well on graphs of a small density.


Combinatorial optimization Independent set problem  Heuristics Notion of a tolerance 



All authors are partially supported by LATNA Laboratory, NRU HSE, RF government grant, ag. 11.G34.31.0057. This study comprises research findings of the first two authors from the “Calculus of tolerances for combinatorial optimization problems: theory and algorithms” project carried out within the Higher School of Economics’ 2011–2012 Academic Fund Program. This research was supported by the Federal Target Program “Research and educational specialists of innovative Russia for 2009–2012”, state contract No 14.B37.21.0393.


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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • B. I. Goldengorin
    • 1
    • 2
  • D. S. Malyshev
    • 1
    • 3
    • 4
    Email author
  • P. M. Pardalos
    • 1
    • 5
  • V. A. Zamaraev
    • 1
    • 3
    • 4
  1. 1.Laboratory of Algorithms and Technologies for Network AnalysisNational Research University Higher School of EconomicsNizhny NovgorodRussia
  2. 2.Department of Mathematics, Subdepartment of Higher MathematicsNational Research University Higher School of EconomicsMoscowRussia
  3. 3.Department of Applied Mathematics and InformaticsNational Research University Higher School of EconomicsNizhny NovgorodRussia
  4. 4.Department of Mathematical Logic and Higher AlgebraLobachevsky State University of Nizhny NovgorodNizhny NovgorodRussia
  5. 5.Department of Industrial and System Engineering, Faculty of Engineering, Center for Applied OptimizationUniversity of FloridaGainesvilleUSA

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