• DocumentCode
    2963315
  • Title

    Organizational evolutionary applied on geometric constraints solving

  • Author

    Wang, Duo ; Li, Wenhui ; Yi, RongQing ; Cheng, X.

  • Author_Institution
    Coll. of Comput. Sci. & Technol., Jilin Univ., Changchun
  • fYear
    2008
  • fDate
    9-10 Sept. 2008
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    In this paper, a new optimization method, Organizational Evolutionary Algorithm (OEA), is proposed, in which a population is made of organizations and whose evolution is led by three organizational evolutionary operators, i.e. the splitting operator, the merging operator and the cooperating operator; the splitting operator controls the size of organizations and make part of organizations enter into next generation directly, which are benefit for keeping the diversity of populations; the merging operator acts as a local searching function with taking advantage of leaders information; the cooperating operator increases the adaptability degree through the interactions of organizations. OEA is successfully applied to solve the non-linear parameterization design problems. Experiments show that OEA performs better than original Generic algorithm (GA) in this application of parameterization design.
  • Keywords
    evolutionary computation; mathematical operators; optimisation; search problems; cooperating operator; geometric constraints solving; local searching function; merging operator; nonlinear parameterization design problem; optimization method; organizational evolutionary algorithm; organizational evolutionary operator; splitting operator; Algorithm design and analysis; Evolutionary computation; Genetic algorithms; Machine learning; Machine learning algorithms; Merging; Neural networks; Nonlinear equations; Optimization methods; Size control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cybernetic Intelligent Systems, 2008. CIS 2008. 7th IEEE International Conference on
  • Conference_Location
    London
  • Print_ISBN
    978-1-4244-2914-1
  • Electronic_ISBN
    978-1-4244-2915-8
  • Type

    conf

  • DOI
    10.1109/UKRICIS.2008.4798970
  • Filename
    4798970