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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/44556

    Title: Using a hybrid genetic algorithm-simulated annealing algorithm for fuzzy programming of reservoir operation
    Authors: Chiu, Yu-chen;張麗秋;Chang, Li-chiu;Chang, Fi-john
    Contributors: 淡江大學水資源及環境工程學系
    Keywords: genetic algorithm;simulated annealing;hybrid GA-SA;reservoir operation;fuzzy programming
    Date: 2007-11
    Issue Date: 2010-03-26 16:18:03 (UTC+8)
    Publisher: Bognor Regis: John Wiley & Sons Ltd.
    Abstract: We present a novel approach for optimizing reservoir operation through fuzzy programming and a hybrid evolution algorithm, i.e. genetic algorithm (GA) with simulated annealing (SA). In the analysis, objectives and constraints of reservoir operation are transformed by fuzzy programming for searching the optimal degree of satisfaction. In the hybrid search procedure, the GA provides a global search and the SA algorithm provides local search. This approach was investigated to search the optimizing operation scheme of Shihmen Reservoir in Taiwan. Monthly inflow data for three years reflecting different hydrological conditions and a consecutive 10-year period were used. Comparisons were made with the existing M-5 reservoir operation rules. The results demonstrate that: (1) fuzzy programming could effectively formulate the reservoir operation scheme into degree of satisfaction α among the users and constraints; (2) the hybrid GA-SA performed much better than the current M-5 operating rules. Analysis also found the hybrid GA-SA conducts parallel analyses that increase the probability of finding an optimal solution while reducing computation time for reservoir operation.
    Relation: Hydrological Processes 21(23), pp.3162-3172
    DOI: 10.1002/hyp.6539
    Appears in Collections:[Graduate Institute & Department of Water Resources and Environmental Engineering] Journal Article

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