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Water 2018, 10(1), 87; https://doi.org/10.3390/w10010087

An Ameliorative Whale Optimization Algorithm for Multi-Objective Optimal Allocation of Water Resources in Handan, China

1
School of Water Conservancy and Hydroelectric Power, Hebei University of Engineering, Handan 056021, China
2
School of Earth Science and Engineering, Hebei University of Engineering, Handan 056038, China
3
Research Center for Water Ecological Civilization & Social Governance of Hebei Province, Handan 056021, China
*
Authors to whom correspondence should be addressed.
Received: 15 November 2017 / Revised: 4 January 2018 / Accepted: 16 January 2018 / Published: 19 January 2018
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Abstract

With the deepening discrepancy between water supply and demand caused by water shortages, alleviating water shortages by optimizing water resource allocation has received extensive attention. How to allocate water resources optimally, rapidly, and effectively has become a challenging problem. Thus, this study employs a meta-heuristic swarm-based algorithm, the whale optimization algorithm (WOA). To overcome drawbacks like relatively low convergence precision and convergence rates, when applying the WOA algorithm to complex optimization problems, logistic mapping is used to initialize swarm location, and inertia weighting is employed to improve the algorithm. The resulting ameliorative whale optimization algorithm (AWOA) shows substantially enhanced convergence rates and precision than the WOA and particle swarm optimization algorithms, demonstrating relatively high reliability and applicability. A water resource allocation optimization model with optimal economic efficiency and least total water shortage volume is established for Handan, China, and solved by the AWOA. The allocation results better reflect actual water usage in Handan. In 2030, the p = 50% total water shortage is forecast as 404.34 × 106 m3 or 14.8%. The shortage is mainly in the primary agricultural sector. The allocation results provide a reference for regional water resources management. View Full-Text
Keywords: water resources; optimal allocation; multi-objective; WOA; AWOA water resources; optimal allocation; multi-objective; WOA; AWOA
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Yan, Z.; Sha, J.; Liu, B.; Tian, W.; Lu, J. An Ameliorative Whale Optimization Algorithm for Multi-Objective Optimal Allocation of Water Resources in Handan, China. Water 2018, 10, 87.

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