• DocumentCode
    1643789
  • Title

    A genetic algorithm for the multi-source and multi-sink minimum vertex cut problem and its applications

  • Author

    Tang, M. ; Fidge, C.J.

  • Author_Institution
    Fac. of Sci. & Technol., Queensland Univ. of Technol., Brisbane, QLD
  • fYear
    2009
  • Firstpage
    3226
  • Lastpage
    3233
  • Abstract
    We present a new penalty-based genetic algorithm for the multi-source and multi-sink minimum vertex cut problem, and illustrate the algorithm´s usefulness with two real-world applications. It is proved in this paper that the genetic algorithm always produces a feasible solution by exploiting some domain-specific knowledge. The genetic algorithm has been implemented on the example applications and evaluated to show how well it scales as the problem size increases.
  • Keywords
    directed graphs; genetic algorithms; minimisation; set theory; combinatorial optimization problem; multisink minimum vertex cut problem; multisource minimum vertex cut problem; penalty-based genetic algorithm; set theory; weighted directed graph; Algorithm design and analysis; Application software; Australia Council; Circuits; Genetic algorithms; Information analysis; Information security; Open source software; Software tools; Throughput;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2009. CEC '09. IEEE Congress on
  • Conference_Location
    Trondheim
  • Print_ISBN
    978-1-4244-2958-5
  • Electronic_ISBN
    978-1-4244-2959-2
  • Type

    conf

  • DOI
    10.1109/CEC.2009.4983353
  • Filename
    4983353