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Open AccessArticle

Multi-Objective Optimal Allocation of Urban Water Resources While Considering Conflict Resolution Based on the PSO Algorithm: A Case Study of Kunming, China

by 1,2,*, 2, 2, 1,2 and 2
1
State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China
2
Business School, Hohai University, Nanjing 211100, China
*
Author to whom correspondence should be addressed.
Sustainability 2020, 12(4), 1337; https://doi.org/10.3390/su12041337
Received: 22 December 2019 / Revised: 2 February 2020 / Accepted: 3 February 2020 / Published: 12 February 2020
(This article belongs to the Special Issue Water Resources and Green Growth)
With the rapid increase of water demand in urban life, ecology and production sectors, the problem of water resources allocation has become increasingly prominent. It has hindered the sustainable development of urban areas. Based on the supply of various water sources and the water demand of different water users, a multi-objective optimal allocation model for urban water resources was proposed. The model was solved using the algorithm of particle swarm optimization (PSO). The algorithm has a fast convergence and is both simple and efficient. In this paper, the conflict over Kunming’s water resources allocation was taken as an example. The PSO algorithm was used to obtain optimized water resources allocation plans in the year 2020 and 2030, under the circumstances of a dry year (inflow guarantee rate p = 0.825) and an unusually dry year (inflow guarantee rate p = 0.885), respectively. The results showed that those allocation plans can lower the future potential water shortage rates of Kunming. At the same time, the interests of different sectors can all be satisfied. Therefore, conflicts over urban water use can be effectively alleviated. View Full-Text
Keywords: conflict resolution; Kunming; multi-objective optimal allocation; particle swarm optimization (PSO); urban water resources conflict resolution; Kunming; multi-objective optimal allocation; particle swarm optimization (PSO); urban water resources
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MDPI and ACS Style

Chen, J.; Yu, C.; Cai, M.; Wang, H.; Zhou, P. Multi-Objective Optimal Allocation of Urban Water Resources While Considering Conflict Resolution Based on the PSO Algorithm: A Case Study of Kunming, China. Sustainability 2020, 12, 1337.

AMA Style

Chen J, Yu C, Cai M, Wang H, Zhou P. Multi-Objective Optimal Allocation of Urban Water Resources While Considering Conflict Resolution Based on the PSO Algorithm: A Case Study of Kunming, China. Sustainability. 2020; 12(4):1337.

Chicago/Turabian Style

Chen, Junfei; Yu, Cong; Cai, Miao; Wang, Huimin; Zhou, Pei. 2020. "Multi-Objective Optimal Allocation of Urban Water Resources While Considering Conflict Resolution Based on the PSO Algorithm: A Case Study of Kunming, China" Sustainability 12, no. 4: 1337.

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