干旱区生态环境知识资源中心(Arid): f-MOPSO/Div: an improved extreme-point-based multi-objective PSO algorithm applied to a socio-economic-environmental conjunctive water use problem

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DOI	10.1007/s10661-020-08727-y
	f-MOPSO/Div: an improved extreme-point-based multi-objective PSO algorithm applied to a socio-economic-environmental conjunctive water use problem
	Rezaei, Farshad; Safavi, Hamid R.
通讯作者	Safavi, HR
来源期刊	ENVIRONMENTAL MONITORING AND ASSESSMENT
ISSN	0167-6369
EISSN	1573-2959
出版年	2020
卷号	192 期号:12
英文摘要	In this paper, a new version of the multi-objective particle swarm optimizer named the Diversity-enhanced fuzzy multi-objective particle swarm optimization (f-MOPSO/Div) algorithm is proposed. This algorithm is an improved version of our recently proposed f-MOPSO. In the proposed algorithm, a new characteristic of the particles in the objective space, which we named the extremity, is also evaluated, along with the Pareto dominance, to appoint proper guides for the particles in the search space. Three improvements are applied to the f-MOPSO to mitigate its shortcomings, generating f-MOPSO/Div: (1) selecting the global best solution based on the diversity of the extreme solutions, (2) impeding the particles to be trapped in the local optima using a mutation scheme based on the dynamic probability, and (3) removing the pre-optimization process. To validate f-MOPSO/Div, it was compared with some other popular multi-objective algorithms on 14 standard low- and high-dimensional test problem suites. After the comparative results indicated the outperformance of the proposal, the f-MOPSO/Div was applied to solve an optimal conjunctive water use management problem, in a semi-arid study area in west-central Iran, over a 13-year long-term planning period with two main objectives: (1) maximizing the aquifer sustainability as an environmental goal, and (2) maximizing the crop yields as a socio-economic goal. As the results suggest, the cumulative groundwater level drawdown is considerably decreased over the whole planning period to make the aquifer sustainable, while the water productivity is held at a desirable level, demonstrating the superiority of the f-MOPSO/Div when also applied to solve a large-scale real-world optimization problem.
英文关键词	Evolutionary optimization Multi-objective optimization Particle swarm optimization Fuzzy inference system Conjunctive water use
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000595115900002
WOS关键词	PARTICLE SWARM OPTIMIZATION ; GENETIC ALGORITHM ; NEURAL-NETWORK ; SURFACE ; DOMINANCE
WOS类目	Environmental Sciences
WOS研究方向	Environmental Sciences & Ecology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/327815
作者单位	[Rezaei, Farshad; Safavi, Hamid R.] Isfahan Univ Technol, Dept Civil Engn, Esfahan, Iran
推荐引用方式 GB/T 7714	Rezaei, Farshad,Safavi, Hamid R.. f-MOPSO/Div: an improved extreme-point-based multi-objective PSO algorithm applied to a socio-economic-environmental conjunctive water use problem[J],2020,192(12).
APA	Rezaei, Farshad,&Safavi, Hamid R..(2020).f-MOPSO/Div: an improved extreme-point-based multi-objective PSO algorithm applied to a socio-economic-environmental conjunctive water use problem.ENVIRONMENTAL MONITORING AND ASSESSMENT,192(12).
MLA	Rezaei, Farshad,et al."f-MOPSO/Div: an improved extreme-point-based multi-objective PSO algorithm applied to a socio-economic-environmental conjunctive water use problem".ENVIRONMENTAL MONITORING AND ASSESSMENT 192.12(2020).