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Urban Water Supply Optimization Scheduling Based on Cuckoo Optimization Algorithm
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Qi-kai MENG1, Yong-zhi CHI1, Can-can JIANG2, 3, Ru-yuan JIAO2, Yi HE2, 4, Xiao-xu ZHENG2, 4, Xiao-qing FU4, Xu-liang ZHUANG2, 3, Sheng-jun XU2, 3, 4
Water Resources and Power | 2026, 44(1) : 152 - 156
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Water Resources and Power | 2026, 44(1): 152-156
Urban Water Supply Optimization Scheduling Based on Cuckoo Optimization Algorithm
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Qi-kai MENG1, Yong-zhi CHI1, Can-can JIANG2, 3, Ru-yuan JIAO2, Yi HE2, 4, Xiao-xu ZHENG2, 4, Xiao-qing FU4, Xu-liang ZHUANG2, 3, Sheng-jun XU2, 3, 4
Affiliations
  • 1.School of Environmental and Municipal Engineering, Tianjin Chengjian University, Tianjin 300384, China
  • 2.Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
  • 3.College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
  • 4.Yangtze River Delta Research Center for Eco-Environmental Sciences, Yiwu 322000, China
Published: 2026-01-25 doi: 10.20040/j.cnki.1000-7709.2026.20242370
Outline
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The effective utilization of digital simulation technology for the synergistic optimization of secondary water supply systems and urban main water supply systems has emerged as a critical necessity in the water supply sector. This optimization aims to achieve leakage control in pipelines and reduce energy consumption while aligning with carbon neutrality objectives. This study presents a comprehensive approach that incorporates the sum of water charges and electricity costs as the objective function, leveraging a combination of EPANET 2.2, MATLAB, and the EPANET-MATLAB Toolkit. We propose an optimization model that employs the Cuckoo Search Algorithm to facilitate the real-time scheduling of pump operations and inflow rates within the secondary water supply system. The proposed optimization model was validated through application to a small-scale water supply network. The results show that the total costs reduce 3.5% over a 24-hour period, with water charges decreasing by 0.63% and electricity costs decreasing by 9.9%. The developed optimization model serves as a significant reference for the future advancement of green, safe, and intelligent water supply management practices.

water distribution system optimization  /  pump and tank scheduling  /  leakage control  /  energy management  /  Cuckoo optimization algorithm
孟琦凯, 池勇志, 姜参参, 焦茹媛, 何怡, 郑效旭, 付晓青, 庄绪亮, 徐圣君. 基于布谷鸟优化算法的城市供水优化调度. 水电能源科学, 2026 , 44 (1) : 152 -156 . DOI: 10.20040/j.cnki.1000-7709.2026.20242370
Qi-kai MENG, Yong-zhi CHI, Can-can JIANG, Ru-yuan JIAO, Yi HE, Xiao-xu ZHENG, Xiao-qing FU, Xu-liang ZHUANG, Sheng-jun XU. Urban Water Supply Optimization Scheduling Based on Cuckoo Optimization Algorithm[J]. Water Resources and Power, 2026 , 44 (1) : 152 -156 . DOI: 10.20040/j.cnki.1000-7709.2026.20242370
Year 2026 volume 44 Issue 1
96
14
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Article Info
doi: 10.20040/j.cnki.1000-7709.2026.20242370
  • Receive Date:2024-12-19
  • Online Date:2026-09-28
  • Published:2026-01-25
Article Data
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History
  • Received:2024-12-19
  • Revised:2025-03-27
  • Accepted:2025-04-18
Funding
Affiliations
    1.School of Environmental and Municipal Engineering, Tianjin Chengjian University, Tianjin 300384, China
    2.Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
    3.College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
    4.Yangtze River Delta Research Center for Eco-Environmental Sciences, Yiwu 322000, China
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表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
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属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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