• DocumentCode
    257492
  • Title

    An evolutionary algorithm with double strategy for global optimization problems

  • Author

    Jianqin Liu ; Ning Li ; Yang Zhao

  • Author_Institution
    Dept. of Int. Educ., Shijiazhuang Inf. Eng. Vocational Coll., Shijiazhuang, China
  • fYear
    2014
  • fDate
    4-6 June 2014
  • Firstpage
    241
  • Lastpage
    244
  • Abstract
    In this paper, we propose a novel evolutionary algorithm with double strategy (DSEA), and prove the asymptotic convergence of DSEA by using the Markov-chain theory. For five high dimension Benchmark functions, the simulation calculation shows that DSEA is superior to PSO and DE, and it is very suitable to solve the global optimization problems.
  • Keywords
    Markov processes; convergence; evolutionary computation; optimisation; DSEA; Markov-chain theory; asymptotic convergence; evolutionary algorithm with double strategy; global optimization problems; high dimension benchmark functions; Sociology; Statistics; Evolutionary algorithm; asymptotic convergence; benchmark functions; double strategy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer and Information Science (ICIS), 2014 IEEE/ACIS 13th International Conference on
  • Conference_Location
    Taiyuan
  • Type

    conf

  • DOI
    10.1109/ICIS.2014.6912141
  • Filename
    6912141
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=257492