Multi-Objective Optimal Allocation of Regional Water Resources Based on the Improved NSGA-III Algorithm

Rapid socio-economic development has intensified the conflict between supply and demand for regional water resources, necessitating optimized water resource allocation to enhance water security. This study establishes a multi-objective water resource optimization model by comprehensively considering...

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Main Authors: Yuhao Wang, Yi Wang, Bin He
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Applied Sciences
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Online Access:https://www.mdpi.com/2076-3417/15/11/5963
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author Yuhao Wang
Yi Wang
Bin He
author_facet Yuhao Wang
Yi Wang
Bin He
author_sort Yuhao Wang
collection DOAJ
description Rapid socio-economic development has intensified the conflict between supply and demand for regional water resources, necessitating optimized water resource allocation to enhance water security. This study establishes a multi-objective water resource optimization model by comprehensively considering economic, social, and ecological benefits. Based on the Non-dominated Sorting Genetic Algorithm-III (NSGA-III), we propose the I-NSGA-III algorithm by integrating reference point improvement strategies, dynamic retention of high-quality solutions, and optimized selection strategies to solve the multi-objective optimization model. A multi-system coupling coordination evaluation model is constructed to assess the final allocation schemes. Compared with some commonly used multi-objective algorithms and tested using the DTLZ series functions, the proposed algorithm demonstrates improved overall performance. Specifically, the IGD indicator decreases by 5.17–50.22%, and the HV indicator increases by 2.71–25.51% compared to NSGA-III. The proposed model is applied to Jinzhong City, China, with four scenarios set for the years 2030 and 2035 at P = 50% and P = 75% to derive reasonable water resource allocation schemes. The results show that the economic benefits range from 161.94 × 10<sup>8</sup> to 212.74 × 10<sup>8</sup> CNY, the water shortage rate is controlled between 1.38% and 10.86%, and COD emissions are maintained between 6.03 × 10<sup>4</sup> and 6.91 × 10<sup>4</sup> tons. Except for the 2030 drought scenario (P = 75%) with a coordination degree of 0.7847, classified as a medium coordination level, all other scenarios have coordination degrees greater than 0.8, indicating a good coordination level. The optimized allocation scheme can serve as a reference for the rational allocation of water resources in Jinzhong City. Moreover, the method proposed in this paper is a general approach that can be extended to other similar water-scarce cities with appropriate parameter adjustments, contributing to the sustainable development of urban water resources.
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spelling doaj-art-50a32372e7c644f2a5bf8f07eacb354d2025-08-20T02:23:00ZengMDPI AGApplied Sciences2076-34172025-05-011511596310.3390/app15115963Multi-Objective Optimal Allocation of Regional Water Resources Based on the Improved NSGA-III AlgorithmYuhao Wang0Yi Wang1Bin He2School of Water Resources and Hydropower Engineering, North China Electric Power University, Beijing 102206, ChinaSchool of Water Resources and Hydropower Engineering, North China Electric Power University, Beijing 102206, ChinaCollege of Civil Engineering and Geographical Environment, Ningbo University, Ningbo 315211, ChinaRapid socio-economic development has intensified the conflict between supply and demand for regional water resources, necessitating optimized water resource allocation to enhance water security. This study establishes a multi-objective water resource optimization model by comprehensively considering economic, social, and ecological benefits. Based on the Non-dominated Sorting Genetic Algorithm-III (NSGA-III), we propose the I-NSGA-III algorithm by integrating reference point improvement strategies, dynamic retention of high-quality solutions, and optimized selection strategies to solve the multi-objective optimization model. A multi-system coupling coordination evaluation model is constructed to assess the final allocation schemes. Compared with some commonly used multi-objective algorithms and tested using the DTLZ series functions, the proposed algorithm demonstrates improved overall performance. Specifically, the IGD indicator decreases by 5.17–50.22%, and the HV indicator increases by 2.71–25.51% compared to NSGA-III. The proposed model is applied to Jinzhong City, China, with four scenarios set for the years 2030 and 2035 at P = 50% and P = 75% to derive reasonable water resource allocation schemes. The results show that the economic benefits range from 161.94 × 10<sup>8</sup> to 212.74 × 10<sup>8</sup> CNY, the water shortage rate is controlled between 1.38% and 10.86%, and COD emissions are maintained between 6.03 × 10<sup>4</sup> and 6.91 × 10<sup>4</sup> tons. Except for the 2030 drought scenario (P = 75%) with a coordination degree of 0.7847, classified as a medium coordination level, all other scenarios have coordination degrees greater than 0.8, indicating a good coordination level. The optimized allocation scheme can serve as a reference for the rational allocation of water resources in Jinzhong City. Moreover, the method proposed in this paper is a general approach that can be extended to other similar water-scarce cities with appropriate parameter adjustments, contributing to the sustainable development of urban water resources.https://www.mdpi.com/2076-3417/15/11/5963improved NSGA-III algorithmwater resource optimization allocationmulti-objective modelcoupling coordination evaluationJinzhong City
spellingShingle Yuhao Wang
Yi Wang
Bin He
Multi-Objective Optimal Allocation of Regional Water Resources Based on the Improved NSGA-III Algorithm
Applied Sciences
improved NSGA-III algorithm
water resource optimization allocation
multi-objective model
coupling coordination evaluation
Jinzhong City
title Multi-Objective Optimal Allocation of Regional Water Resources Based on the Improved NSGA-III Algorithm
title_full Multi-Objective Optimal Allocation of Regional Water Resources Based on the Improved NSGA-III Algorithm
title_fullStr Multi-Objective Optimal Allocation of Regional Water Resources Based on the Improved NSGA-III Algorithm
title_full_unstemmed Multi-Objective Optimal Allocation of Regional Water Resources Based on the Improved NSGA-III Algorithm
title_short Multi-Objective Optimal Allocation of Regional Water Resources Based on the Improved NSGA-III Algorithm
title_sort multi objective optimal allocation of regional water resources based on the improved nsga iii algorithm
topic improved NSGA-III algorithm
water resource optimization allocation
multi-objective model
coupling coordination evaluation
Jinzhong City
url https://www.mdpi.com/2076-3417/15/11/5963
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