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Application of F-HGAPSO Algorithm in Reservoir Flood Control Optimal Operation

Author

Listed:
  • Guangyun Cui

    (Shandong University)

  • Zhen Qi

    (Shandong University)

  • Huaqing Zhao

    (Shandong University)

  • Ranhang Zhao

    (Shandong University)

  • Haofang Wang

    (Shandong University)

  • Jiaxing Zhao

    (Shandong University)

Abstract

Flood control operation of reservoir is a high-dimensional and nonlinear problem with numerous constraints, and intelligent algorithms are widely used to solve the flood control optimization problem. The traditional intelligent algorithms often face issues such as slow convergence and a tendency to find local optima when solving flood control optimization problems. This paper proposes a method that couples a hybrid genetic algorithm-particle swarm optimization with fuzzy adaptive inertia weights (F-HGAPSO) to solve the model established for reservoir flood control operation. The initial population is generated from the reservoir discharge taking as the decision variable, initially optimized using the genetic algorithm, and then further optimized to obtain the results using the particle swarm optimization (PSO) with a Mamdani fuzzy system for adaptive inertia weight. Finally, as a case study, the proposed method is applied to solve the model established for Mushan reservoir flood control operation, with a penalty function handling the constraints. To demonstrate the validity of the method, the results obtained by F-HGAPSO are compared and analyzed with those obtained by PSO and the elite genetic algorithm (EGA). The results show that F-HGAPSO outperforms PSO and EGA in solving the flood control model, achieving peak flow reductions of 20.28%-30.27% with rapid convergence in 13–22 iterations, effectively avoiding local optima issues, and that highlights the F—HGAPSO has strong optimization ability and efficiency. The proposed method can be extended to the flood control operation of other reservoirs with similar conditions.

Suggested Citation

  • Guangyun Cui & Zhen Qi & Huaqing Zhao & Ranhang Zhao & Haofang Wang & Jiaxing Zhao, 2025. "Application of F-HGAPSO Algorithm in Reservoir Flood Control Optimal Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 39(4), pages 1763-1782, March.
    • Handle: RePEc:spr:waterr:v:39:y:2025:i:4:d:10.1007_s11269-024-04045-x
    DOI: 10.1007/s11269-024-04045-x
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    References listed on IDEAS

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    1. Ji He & Wen Guo & Songlin Wang & Haitao Chen & Xiaoqi Guo & Shumin Li, 2024. "Application of Multi-Strategy Based Improved DBO Algorithm in Optimal Scheduling of Reservoir Groups," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 38(6), pages 1883-1901, April.
    2. Fuxin Chai & Feng Peng & Hongping Zhang & Wenbin Zang, 2023. "Stable Improved Dynamic Programming Method: An Efficient and Accurate Method for Optimization of Reservoir Flood Control Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(14), pages 5635-5654, November.
    3. Xuan Li & Xiaoping Zhou & Jingming Hou & Yuan Liu & Shuhong Xue & Huan Ma & Bowen Su, 2024. "A Hydrodynamic Model and Data-Driven Evolutionary Multi-Objective Optimization Algorithm Based Optimal Operation Method for Multi-barrage Flood Control," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 38(11), pages 4323-4341, September.
    4. Suiling Wang & Zhiqiang Jiang & Yi Liu, 2022. "Dimensionality Reduction Method of Dynamic Programming under Hourly Scale and Its Application in Optimal Scheduling of Reservoir Flood Control," Energies, MDPI, vol. 15(3), pages 1-17, January.
    5. Saïd Salhi & Jonathan Thompson, 2022. "An Overview of Heuristics and Metaheuristics," Springer Books, in: Saïd Salhi & John Boylan (ed.), The Palgrave Handbook of Operations Research, chapter 0, pages 353-403, Springer.
    6. Ji He & Xiaoqi Guo & Haitao Chen & Fuxin Chai & Shengming Liu & Hongping Zhang & Wenbin Zang & Songlin Wang, 2023. "Application of HSMAAOA Algorithm in Flood Control Optimal Operation of Reservoir Groups," Sustainability, MDPI, vol. 15(2), pages 1-16, January.
    7. Umut Güvengir & Secil Savasaneril & A. Burcu Altan-Sakarya & Serkan Buhan, 2021. "Short-Term Flood Control and Long-Term Energy Maximization in Multi-reservoir Systems Using Improved Particle Swarm Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(13), pages 4293-4307, October.
    8. Huaqing Zhao & Hao Wang & Yuxuan Zhang & Ranhang Zhao & Zhen Qi & Haodong Zhang, 2024. "Flash Flood Simulation for Hilly Reservoirs Considering Upstream Reservoirs—A Case Study of Moushan Reservoir," Sustainability, MDPI, vol. 16(12), pages 1-23, June.
    9. Saad Dahmani & Djilali Yebdri, 2020. "Hybrid Algorithm of Particle Swarm Optimization and Grey Wolf Optimizer for Reservoir Operation Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(15), pages 4545-4560, December.
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