• DocumentCode
    618043
  • Title

    Structured Population Size Reduction Differential Evolution with Multiple Mutation Strategies on CEC 2013 real parameter optimization

  • Author

    Zamuda, A. ; Brest, J. ; Mezura-Montes, Efren

  • Author_Institution
    Fac. of Electr. Eng. & Comput. Sci., Univ. of Maribor, Maribor, Slovenia
  • fYear
    2013
  • fDate
    20-23 June 2013
  • Firstpage
    1925
  • Lastpage
    1931
  • Abstract
    This paper presents a differential evolution (DE) algorithm for real-parameter optimization. The algorithm includes the self-adaptive jDE algorithm with one of its strongest extensions, population reduction, combined with multiple mutation strategies using a structured population. The two mutation strategies used are run dependent on the population size, which is reduced with growing function evaluation number. The population is structured with a separate part where only DE/best strategy is executed and then the best vectors are exchanged with the main population part. Algorithm performance assessment results are presented for 10, 30, and 50 dimension settings for all of the 28 problems included in the Problem Definitions and Evaluation Criteria for the CEC 2013 Special Session and Competition on Real-Parameter Optimization.
  • Keywords
    evolutionary computation; CEC 2013 real parameter optimization; DE algorithm; growing function evaluation number; multiple mutation strategy; self-adaptive jDE algorithm; structured population size reduction differential evolution; Educational institutions; Evolutionary computation; Indexes; Optimization; Sociology; Statistics; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation (CEC), 2013 IEEE Congress on
  • Conference_Location
    Cancun
  • Print_ISBN
    978-1-4799-0453-2
  • Electronic_ISBN
    978-1-4799-0452-5
  • Type

    conf

  • DOI
    10.1109/CEC.2013.6557794
  • Filename
    6557794