A knee point-driven many-objective pigeon-inspired optimization algorithm

doi:10.1007/s40747-022-00706-9

CORC > 自动化研究所 > 中国科学院自动化研究所 > 精密感知与控制研究中心 > 人工智能与机器学习

	A knee point-driven many-objective pigeon-inspired optimization algorithm
	Zhao, Lihong 2; Ren, Yeqing 3; Zeng, Youqian 2; Cui, Zhihua 2; Zhang, Wensheng 1
刊名	COMPLEX & INTELLIGENT SYSTEMS
	2022-03-31
页码	23
关键词	Knee point Knee-oriented dominance Many-objective optimization Pigeon-inspired algorithm Preference
ISSN号	2199-4536
DOI	10.1007/s40747-022-00706-9
通讯作者	Cui, Zhihua(cuizhihua@tyust.edu.cn)
英文摘要	The number of solutions obtained is too large to provide a set of solutions with good performance in the nearby area of the true Pareto front when problem-specific preferences are unavailable. Therefore, this paper proposes a knee point-driven many-objective pigeon-inspired optimization algorithm (KnMAPIO). An environmental selection strategy based on knee-oriented dominance is proposed to improve selection pressure and population diversity. In addition, a new velocity updating equation with Gaussian distribution, Cauchy distribution and Levy distribution is proposed in this paper to provide new search directions and reduce the possibility of falling into local optima. Two types of experiments are carried out in this paper: one is to compare the proposed method with four other algorithms on the knee-oriented benchmark PMOPs to verify the algorithm's performance in detecting the knee points and the knee region; another is to compare the proposed method with eight other state-of-the-art algorithms on the classic benchmark DTLZ and WFG. The results of both experiments verify the effectiveness of the proposed algorithm and the ability to approximate to the true Pareto front.
资助项目	National Key Research and Development Program of China[2018YFC1604000] ; National Natural Science Foundation of China[61806138] ; National Natural Science Foundation of China[61772478] ; National Natural Science Foundation of China[U1636220] ; National Natural Science Foundation of China[61961160707] ; National Natural Science Foundation of China[61976212] ; Key R&D program of Shanxi Province (High Technology)[201903D121119] ; Key R&D program of Shanxi Province (International Cooperation)[201903D421048] ; Key R&D program (international science and technology cooperation project) of Shanxi Province[201903D421003]
WOS关键词	PARTICLE SWARM OPTIMIZATION ; MULTIOBJECTIVE EVOLUTIONARY ALGORITHM ; COLONY
WOS研究方向	Computer Science
语种	英语
出版者	SPRINGER HEIDELBERG
WOS记录号	WOS:000777366100002
资助机构	National Key Research and Development Program of China ; National Natural Science Foundation of China ; Key R&D program of Shanxi Province (High Technology) ; Key R&D program of Shanxi Province (International Cooperation) ; Key R&D program (international science and technology cooperation project) of Shanxi Province
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/48271]
专题	精密感知与控制研究中心_人工智能与机器学习
通讯作者	Cui, Zhihua
作者单位	1.Chinese Acad Sci, Inst Automat, State Key Lab Intelligent Control & Management Co, Beijing, Peoples R China 2.Taiyuan Univ Sci & Technol, Sch Comp Sci & Technol, Taiyuan, Peoples R China 3.Beijing Univ Posts & Telecommun, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Zhao, Lihong,Ren, Yeqing,Zeng, Youqian,et al. A knee point-driven many-objective pigeon-inspired optimization algorithm[J]. COMPLEX & INTELLIGENT SYSTEMS,2022:23.
APA	Zhao, Lihong,Ren, Yeqing,Zeng, Youqian,Cui, Zhihua,&Zhang, Wensheng.(2022).A knee point-driven many-objective pigeon-inspired optimization algorithm.COMPLEX & INTELLIGENT SYSTEMS,23.
MLA	Zhao, Lihong,et al."A knee point-driven many-objective pigeon-inspired optimization algorithm".COMPLEX & INTELLIGENT SYSTEMS (2022):23.