• DocumentCode
    2709377
  • Title

    Modified gravitational search algorithm

  • Author

    Kazak, Nihan ; Duysak, Alpaslan

  • Author_Institution
    Dept. of Comput. Eng., Bilecik Seyh Edebali Univ., Bilecik, Turkey
  • fYear
    2012
  • fDate
    2-4 July 2012
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    In this paper, we present an efficient algorithm for solving optimization problems, which is based on gravitational search algorithm. In the proposed algorithm, called Member-Satellite algorithm, satellites have been appointed to all the agents which called as members in proposed algorithm. Members and their satellites are used to find a near optimal solution all together. The algorithm is continued with members or satellites with the best fitness value. Three benchmark functions are used to evaluate and to compare performance of the presented algorithm with GSA. The obtained results confirm the high performance of the proposed method in solving various nonlinear functions.
  • Keywords
    optimisation; search problems; GSA; benchmark functions; best fitness value; member-satellite algorithm; modified gravitational search algorithm; nonlinear functions; optimization problems; performance evaluation; Algorithm design and analysis; Benchmark testing; Heuristic algorithms; Optimization; Satellites; Search problems; Sections; gravitational search algorithm; heuristic algorithm; optimization; swarm intelligence;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovations in Intelligent Systems and Applications (INISTA), 2012 International Symposium on
  • Conference_Location
    Trabzon
  • Print_ISBN
    978-1-4673-1446-6
  • Type

    conf

  • DOI
    10.1109/INISTA.2012.6247035
  • Filename
    6247035