• DocumentCode
    2052583
  • Title

    Hybrid genetic algorithm for solving Knapsack problem

  • Author

    Tharanipriya, P.G. ; Vishnuraja, P.

  • Author_Institution
    Kongu Eng. Coll., Perundurai, India
  • fYear
    2013
  • fDate
    21-22 Feb. 2013
  • Firstpage
    416
  • Lastpage
    420
  • Abstract
    In clustering, clustering techniques are applied to get the best solution. The traditional clustering algorithms lead to local optimum. Hybrid genetic algorithm which includes multi clustering genetic algorithm with rough set theory is to be proposed to improve the efficiency and to get the optimal solution. The selection procedure of genetic algorithm has lower efficiency. So rough set theory can be used for selecting chromosomes for further process which is applied in 0-1 Knapsack problem.
  • Keywords
    data mining; genetic algorithms; knapsack problems; pattern clustering; rough set theory; 0-1 knapsack problem; clustering techniques; data mining; hybrid genetic algorithm; multi clustering genetic algorithm; rough set theory; Algorithm design and analysis; Clustering algorithms; Data mining; Evolution (biology); Genetic algorithms; Optimization; Set theory; Genetic Algorithm; Knapsack problem; Multi-clustering genetic algorithm; Rough set Theory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Communication and Embedded Systems (ICICES), 2013 International Conference on
  • Conference_Location
    Chennai
  • Print_ISBN
    978-1-4673-5786-9
  • Type

    conf

  • DOI
    10.1109/ICICES.2013.6508280
  • Filename
    6508280