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Article

Application of AMOGWO in Multi-Objective Optimal Allocation of Water Resources in Handan, China

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School of Water Conservancy and Hydroelectric Power, Hebei University of Engineering, Handan 056021, China
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Hebei Key Laboratory of Intelligent Water Conservancy, Hebei University of Engineering, Handan 056001, China
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School of Earth Science and Engineering, Hebei University of Engineering, Handan 056021, China
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Water Conservancy Management of Handan City, Handan 056021, China
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Runze Water Co., Ltd. of Fengfeng Handan, Handan 056038, China
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Authors to whom correspondence should be addressed.
Academic Editor: Antonio Lo Porto
Water 2022, 14(1), 63; https://doi.org/10.3390/w14010063
Received: 5 November 2021 / Revised: 13 December 2021 / Accepted: 27 December 2021 / Published: 29 December 2021
(This article belongs to the Section Water Resources Management, Policy and Governance)
The reasonable allocation of water resources using different optimization technologies has received extensive attention. However, not all optimization algorithms are suitable for solving this problem because of its complexity. In this study, we applied an ameliorative multi-objective gray wolf optimizer (AMOGWO) to the problem. For AMOGWO, which is based on the multi-objective gray wolf optimizer, we improved the distance control parameter calculation method, added crowding degree for the archive, and optimized the selection mechanism for leader wolves. Subsequently, AMOGWO was used to solve the multi-objective optimal allocation of water resources in Handan, China, for 2035, with the maximum economic benefit and minimum social water shortage used as objective functions. The optimal results obtained indicate a total water demand in Handan of 2740.43 × 106 m3, total water distribution of 2442.23 × 106 m3, and water shortage of 298.20 × 106 m3, which is consistent with the principles of water resource utilization in Handan. Furthermore, comparison results indicate that AMOGWO has substantially enhanced convergence rates and precision compared to the non-dominated sorting genetic algorithm II and the multi-objective particle swarm optimization algorithm, demonstrating relatively high reliability and applicability. This study thus provides a new method for solving the multi-objective optimal allocation of water resources. View Full-Text
Keywords: multi-objective optimization; water resources; optimal allocation; AMOGWO; Handan multi-objective optimization; water resources; optimal allocation; AMOGWO; Handan
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MDPI and ACS Style

Li, S.; Yan, Z.; Sha, J.; Gao, J.; Han, B.; Liu, B.; Xu, D.; Chang, Y.; Han, Y.; Xu, Z.; Sun, B. Application of AMOGWO in Multi-Objective Optimal Allocation of Water Resources in Handan, China. Water 2022, 14, 63. https://doi.org/10.3390/w14010063

AMA Style

Li S, Yan Z, Sha J, Gao J, Han B, Liu B, Xu D, Chang Y, Han Y, Xu Z, Sun B. Application of AMOGWO in Multi-Objective Optimal Allocation of Water Resources in Handan, China. Water. 2022; 14(1):63. https://doi.org/10.3390/w14010063

Chicago/Turabian Style

Li, Su, Zhihong Yan, Jinxia Sha, Jing Gao, Bingqing Han, Bin Liu, Dan Xu, Yifan Chang, Yuhang Han, Zhiheng Xu, and Bolun Sun. 2022. "Application of AMOGWO in Multi-Objective Optimal Allocation of Water Resources in Handan, China" Water 14, no. 1: 63. https://doi.org/10.3390/w14010063

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