• DocumentCode
    2982375
  • Title

    Fast evolutionary programming through search momentum and multiple offspring strategy

  • Author

    Cho, Hyeon-Joong ; Oh, Se-young ; Choi, Doo-Hyun

  • Author_Institution
    Dept. of Electr. Eng., Pohang Inst. of Sci. & Technol., South Korea
  • fYear
    1998
  • fDate
    4-9 May 1998
  • Firstpage
    805
  • Lastpage
    809
  • Abstract
    A new algorithm that helps to accelerate convergence as well as to enhance the diversity of the evolutionary programming (EP) search technique is proposed, based on an individual structure concept. The major components of the algorithm that lie behind its good performance includes scaling, selection strategy, the use of age and the search direction (or momentum) vector, and multiple offspring per parent. Not only are the multiple offspring approach and the search direction vector concept novel but the combination of these features used for EP is also new. Through a benchmark test, its search performance has been found to be superior to the conventional EP and one of its acceleration methods
  • Keywords
    convergence; genetic algorithms; programming; search problems; software performance evaluation; vectors; age; algorithm performance; benchmark test; convergence acceleration; diversity; fast evolutionary programming; individual structure concept; multiple offspring strategy; scaling; search direction vector; search momentum; search performance; selection strategy; Acceleration; Benchmark testing; Convergence; Cost function; Gaussian noise; Genetic algorithms; Genetic mutations; Genetic programming; Life estimation; Noise robustness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on
  • Conference_Location
    Anchorage, AK
  • Print_ISBN
    0-7803-4869-9
  • Type

    conf

  • DOI
    10.1109/ICEC.1998.700155
  • Filename
    700155