• DocumentCode
    1844791
  • Title

    An Improved Genetic Algorithm Based on Variable Step-Size Search

  • Author

    Zhu, Guannan ; Xu, Ning ; An, Zhulin ; Xu, Yongjun

  • Author_Institution
    Wuhan Univ. of Technol., Wuhan
  • fYear
    2008
  • fDate
    18-21 Nov. 2008
  • Firstpage
    1813
  • Lastpage
    1818
  • Abstract
    Genetic algorithms (GAs) are global optimization algorithms which can be used to solve different kinds of problems. However, in the situation that the size of feasible solution space is far less than that of search space, GAs may degrade to random searches. This paper presents an improved genetic algorithm, which adopts variable step-size algorithm to obtain a feasible solution, and reduce search space during the same process. The theoretical analysis and experiments in comparison with the random search are also presented,which indicate that this improved algorithm would reduce the search time in solving problems that have a large search space.
  • Keywords
    genetic algorithms; search problems; global optimization algorithms; improved genetic algorithm; search space; variable step-size search; Algorithm design and analysis; Binary codes; Biological cells; Computers; Degradation; Genetic algorithms; Genetic mutations; Machine learning algorithms; Signal processing algorithms; Space technology; Genetic algorithms; search space reduction; variable step-size;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Young Computer Scientists, 2008. ICYCS 2008. The 9th International Conference for
  • Conference_Location
    Hunan
  • Print_ISBN
    978-0-7695-3398-8
  • Electronic_ISBN
    978-0-7695-3398-8
  • Type

    conf

  • DOI
    10.1109/ICYCS.2008.351
  • Filename
    4709249