• DocumentCode
    1634736
  • Title

    Evolutionary diffusion optimization. II. Performance assessment

  • Author

    Tsui, Kwok Ching ; Liu, Jiming

  • Author_Institution
    Dept. of Comput. Sci., Hong Kong Baptist Univ., Kowloon, China
  • Volume
    2
  • fYear
    2002
  • fDate
    6/24/1905 12:00:00 AM
  • Firstpage
    1284
  • Lastpage
    1289
  • Abstract
    A new population-based stochastic search algorithm called evolutionary diffusion optimization (EDO) inspired by diffusion in nature has been proposed. This article compares the performance of EDO with simulated annealing and fast evolutionary programming. Experimental results show that EDO performs better than SA and FEP in some cases
  • Keywords
    diffusion; evolutionary computation; optimisation; search problems; stochastic processes; evolutionary diffusion optimization; performance assessment; population-based stochastic search algorithm; Ant colony optimization; Computational modeling; Computer science; Cultural differences; Data structures; Evolutionary computation; Genetic programming; Particle swarm optimization; Simulated annealing; Stochastic processes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2002. CEC '02. Proceedings of the 2002 Congress on
  • Conference_Location
    Honolulu, HI
  • Print_ISBN
    0-7803-7282-4
  • Type

    conf

  • DOI
    10.1109/CEC.2002.1004428
  • Filename
    1004428
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1634736