• DocumentCode
    2948913
  • Title

    Multi-objective Fuzzy Mutative Scale Chaos Optimization Algorithm and Application

  • Author

    Wei, Liang ; Zhen, Shi ; Sihui, Wang

  • Author_Institution
    Bus. Sch., Hohai Univ., Changzhou, China
  • fYear
    2011
  • fDate
    20-21 Aug. 2011
  • Firstpage
    93
  • Lastpage
    97
  • Abstract
    Based on the fuzzy mathematics and chaos optimization theory, this paper proposes an algorithm of the Multi-objective Fuzzy Mutative Scale Chaos Optimization Algorithm (MFMSCOA) to solve various types of Multi-objective Optimization Problems (MOP). The multi-objectives optimization problems will ex-press the fuzzy optimization problems by delimiting membership degree functions of objective functions in a fuzzy way. Then, according to the Maximum and minimum rule of the fuzzy set theory, one can transfer a multi-objective optimization problem into a single objective nonlinear programming problem by applying the idea of fuzzy asymmetric method and the biggest satisfaction principle in fuzzy set theory. Lastly, the most sat-is factory solution will be obtained by the application of MFMSCOA. Theoretical analyze and Simulation results show that the proposed MFMSCOA is feasible and effective. It will provide a novel way to solve the multi-objective optimization problems.
  • Keywords
    fuzzy set theory; nonlinear programming; biggest satisfaction principle; chaos optimization theory; fuzzy asymmetric method; fuzzy mathematics theory; fuzzy set theory; membership degree function; multiobjective fuzzy mutative scale chaos optimization algorithm; multiobjective optimization problem; single objective nonlinear programming; Chaos; Hydroelectric power generation; Mathematical model; Optimization; Water resources; Chaos Optimization; Fuzzy Optimization; Multi-objectives; Optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligence Science and Information Engineering (ISIE), 2011 International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4577-0960-9
  • Electronic_ISBN
    978-0-7695-4480-9
  • Type

    conf

  • DOI
    10.1109/ISIE.2011.127
  • Filename
    5997385