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Application of Multi-Strategy Based Improved DBO Algorithm in Optimal Scheduling of Reservoir Groups

Ji He (heji@ncwu.edu.cn), Wen Guo (gw681014@163.com), Songlin Wang (wangsonglin@ncwu.edu.cn), Haitao Chen (chenghaitao@ncwu.edu.cn), Xiaoqi Guo (guoxiaoqi417@163.com) and Shumin Li (xxlshumin@163.com)
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Ji He: North China University of Water Resources and Electric Power
Wen Guo: North China University of Water Resources and Electric Power
Songlin Wang: North China University of Water Resources and Electric Power
Haitao Chen: North China University of Water Resources and Electric Power
Xiaoqi Guo: North China University of Water Resources and Electric Power
Shumin Li: North China University of Water Resources and Electric Power

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2024, vol. 38, issue 6, No 4, 1883-1901

Abstract: Abstract Aiming at the problems of high dimensionality, multi-constraint, multi-phase, non-linearity, and the fact that the established model is not easy to solve for the optimal scheduling of reservoir group flood control, this paper improved the dung beetle optimization algorithm by adopting a variety of strategies, proposes a new intelligent optimization algorithm, the multi-strategy improved dung beetle algorithm (MIDBO), and firstly applied it to the optimal scheduling of flood control in reservoir groups. In addition, this study analyzed and contrasted the MIDBO algorithm's calculation results with the examples of the particle swarm and dung beetle optimization algorithms in relation to the reservoir cluster in the middle and lower sections of the Yellow River. And the peak reduction rates of these algorithms are 52.82%, 51.48%, and 50.25% in turn. The outcomes demonstrate that the MIDBO algorithm has strong performance, fast optimization efficiency, obvious peak reduction effect, and is a feasible method to solve the optimization problem of reservoir flood control and scheduling.

Keywords: Optimal scheduling of flood control in reservoir groups; Group of reservoirs in the middle and lower reaches of the Yellow River; Many strategies; The MIDBO algorithm (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11269-023-03656-0

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