• DocumentCode
    120117
  • Title

    An Improved Cuckoo Search Algorithm with Adaptive Method

  • Author

    Zhenxing Zhang ; Yongjie Chen

  • Author_Institution
    Coll. of Autom., Harbin Eng. Univ., Harbin, China
  • fYear
    2014
  • fDate
    4-6 July 2014
  • Firstpage
    204
  • Lastpage
    207
  • Abstract
    To improve the refining ability and convergence rate of cuckoo search algorithm for finding optimal solution. An improved cuckoo search algorithm with adaptive method is proposed. The self-adaptive machine is used to control the scaling factor and find probability so as to improve population diversity and avoid premature, as a result, more individuals participating in the evolution, and then refining ability and convergence rate are improved. The result of experiment show the ICS algorithm has better performance when lots of test functions are considered, ICS algorithm has faster convergence speed and higher precision.
  • Keywords
    convergence of numerical methods; probability; search problems; ICS algorithm; adaptive method; cuckoo search algorithm; optimal solution; probability; scaling factor; self-adaptive machine; Algorithm design and analysis; Convergence; Educational institutions; Optimization; Particle swarm optimization; Refining; Standards; Cuckoo search algorithm; convergence rate; optimal solution; refining ability; self-adaptive machine;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Sciences and Optimization (CSO), 2014 Seventh International Joint Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4799-5371-4
  • Type

    conf

  • DOI
    10.1109/CSO.2014.45
  • Filename
    6923669