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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/79692


    Title: Multi-objective optimization via fuzzy-evolution method
    Authors: Huang, T. L.;Hwang, T.Y.;Chang, C.H.;Sheu, J.S.;wang, C.T.;Lien, Y.N.;Huang, C.C.;Chen, C.R.
    連耀南
    Contributors: 資科系
    Date: 2010
    Issue Date: 2015-12-21 16:01:56 (UTC+8)
    Abstract: The purpose of this paper is to address the multi-objective optimization via combined fuzzy satisfied method and evolution programming (E.P.) method. The concept of non-inferiority is employed to characterize a solution of the multi-objective problem. Then, a fuzzy satisfied method based on evolutionary programming is introduce d to determine the optimal solution. As a result, the objective functions of the optimization problem are modeled with fuzzy sets to represent their imprecise natur e. That also enables us to reduce the inaccuracies in decision-makers` judgments. A time-sharing computer program is implemented, and an application to a multi-objective operation problem in feeder reconfiguration in electric power systems is demonstrated along with the computer outputs. In conclusion, the proposed solution algorithm allows for a more realistic problem formulation efficiently obtained the optimal solution for the tested system with a large search space.
    Relation: Journal of Information and Optimization Sciences, 31(6), 1263-1274
    Data Type: article
    DOI link: http://dx.doi.org/10.1080/02522667.2010.10700026
    DOI: 10.1080/02522667.2010.10700026
    Appears in Collections:[Department of Computer Science ] Periodical Articles

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