• DocumentCode
    2137041
  • Title

    An improved gravitational search algorithm based on neighbor search

  • Author

    Wang, Chingyue ; Gao, K.Z. ; GUO, Jun

  • Author_Institution
    Coll. of Electr. & Inf. Eng., Yangzhou Polytech. Inst., Yangzhou, China
  • fYear
    2013
  • fDate
    23-25 July 2013
  • Firstpage
    681
  • Lastpage
    685
  • Abstract
    The gravitational search algorithm (GSA) is a new meta-heuristic optimization method based on the law of gravity and mass interactions. An improved GSA (IGSA) is proposed in this paper where a neighbor search is employed to enhance the performance of GSA. The IGSA can obtain a better or best solution in a neighbor space through one or more times random neighbor search. Two different search methods are designed for the proposed improved gravitational search algorithm. In addition, the effect of the gravitational constant to the performance of the IGSA is discussed. Extensive computational experiments are carried out using well-known benchmark functions. Computational results and comparisons show the efficiency and effectiveness of the proposed IGSA.
  • Keywords
    search problems; GSA; improved gravitational search algorithm; meta-heuristic optimization method; neighbor search; Algorithm design and analysis; Benchmark testing; Classification algorithms; Convergence; Educational institutions; Force; Optimization; gravitation search algorithm; meta-heuristic; random neighbor search;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation (ICNC), 2013 Ninth International Conference on
  • Conference_Location
    Shenyang
  • Type

    conf

  • DOI
    10.1109/ICNC.2013.6818062
  • Filename
    6818062