A Many-Objective Evolutionary Algorithm Using A One-by-One Selection Strategy

doi:10.1109/TCYB.2016.2638902

CORC > 兰州理工大学 > 兰州理工大学

	A Many-Objective Evolutionary Algorithm Using A One-by-One Selection Strategy
	Liu, Yiping 2; Gong, Dunwei 2,3; Sun, Jing 1; Jin, Yaochu 4
刊名	IEEE TRANSACTIONS ON CYBERNETICS
	2017-09
卷号	47 期号:9 页码:2689-2702
关键词	Convergence cosine similarity diversity evolutionary multiobjective optimization many-objective optimization performance indicator
ISSN号	2168-2267
DOI	10.1109/TCYB.2016.2638902
英文摘要	Most existing multiobjective evolutionary algorithms experience difficulties in solving many-objective optimization problems due to their incapability to balance convergence and diversity in the high-dimensional objective space. In this paper, we propose a novel many-objective evolutionary algorithm using a one-by-one selection strategy. The main idea is that in the environmental selection, offspring individuals are selected one by one based on a computationally efficient convergence indicator to increase the selection pressure toward the Pareto optimal front. In the one-by-one selection, once an individual is selected, its neighbors are de-emphasized using a niche technique to guarantee the diversity of the population, in which the similarity between individuals is evaluated by means of a distribution indicator. In addition, different methods for calculating the convergence indicator are examined and an angle-based similarity measure is adopted for effective evaluations of the distribution of solutions in the high-dimensional objective space. Moreover, corner solutions are utilized to enhance the spread of the solutions and to deal with scaled optimization problems. The proposed algorithm is empirically compared with eight state-of-the-art many-objective evolutionary algorithms on 80 instances of 16 benchmark problems. The comparative results demonstrate that the overall performance of the proposed algorithm is superior to the compared algorithms on the optimization problems studied in this paper.
资助项目	Joint Research Fund for Overseas Chinese, Hong Kong, and Macao Scholars of National Natural Science Foundation of China[61428302]
WOS研究方向	Automation & Control Systems ; Computer Science
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000407222900030
状态	已发表
内容类型	期刊论文
源URL	[http://119.78.100.223/handle/2XXMBERH/33138]
专题	兰州理工大学
通讯作者	Liu, Yiping
作者单位	1.Huai Hai Inst Technol, Sch Sci, Lianyungang 222005, Peoples R China 2.China Univ Min & Technol, Sch Informat & Elect Engn, Xuzhou 221116, Peoples R China 3.LanZhou Univ Technol, Sch Elect Engn & Informat Engn, Lanzhou 730050, Gansu, Peoples R China 4.Univ Surrey, Dept Comp Sci, Guildford GU2 7XH, Surrey, England
推荐引用方式 GB/T 7714	Liu, Yiping,Gong, Dunwei,Sun, Jing,et al. A Many-Objective Evolutionary Algorithm Using A One-by-One Selection Strategy[J]. IEEE TRANSACTIONS ON CYBERNETICS,2017,47(9):2689-2702.
APA	Liu, Yiping,Gong, Dunwei,Sun, Jing,&Jin, Yaochu.(2017).A Many-Objective Evolutionary Algorithm Using A One-by-One Selection Strategy.IEEE TRANSACTIONS ON CYBERNETICS,47(9),2689-2702.
MLA	Liu, Yiping,et al."A Many-Objective Evolutionary Algorithm Using A One-by-One Selection Strategy".IEEE TRANSACTIONS ON CYBERNETICS 47.9(2017):2689-2702.