• DocumentCode
    3531194
  • Title

    Multi-objective Optimization Evolutionary Algorithm Based on Point-to-Weight Method

  • Author

    Xueqiang Li ; Jiang Wang ; Jing Xiao ; Xiaoling Zhang

  • Author_Institution
    Sch. of Inf. Eng., Dongguan Campus of Guangdong Med. Coll., Dongguan, China
  • fYear
    2013
  • fDate
    9-11 Sept. 2013
  • Firstpage
    191
  • Lastpage
    196
  • Abstract
    Selecting points using min-max strategy can guarantee uniformity of Pareto. But shortcomings are missing effective solutions and poor solutions being selected. By the analysis of choosing points with the min-max strategy and reasonable fitness metric, we propose a new evolutionary method choosing weights on points (point-to-weight). A large number of multi-objective optimization functions have been tested by our algorithm. The graphics and IGD metric results show that our algorithm can effectively solves the complex multi-objective optimization problems.
  • Keywords
    Pareto optimisation; evolutionary computation; minimax techniques; Pareto uniformity; fitness metric; min-max strategy; multiobjective optimization evolutionary algorithm; point-to-weight method; Algorithm design and analysis; Educational institutions; Evolutionary computation; Measurement; Optimization; Sociology; Statistics; evolutionary algorithm; min-max strategy; point-to-weight;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Emerging Intelligent Data and Web Technologies (EIDWT), 2013 Fourth International Conference on
  • Conference_Location
    Xi´an
  • Print_ISBN
    978-1-4799-2140-9
  • Type

    conf

  • DOI
    10.1109/EIDWT.2013.38
  • Filename
    6631616