A two-stage evolutionary strategy based MOEA/D to multi-objective problems

doi:10.1016/j.eswa.2021.115654

	A two-stage evolutionary strategy based MOEA/D to multi-objective problems
	Cao, Jie; Zhang, Jianlin; Zhao, Fuqing; Chen, Zuohan
刊名	Expert Systems with Applications
	2021-12-15
卷号	185
关键词	Multiobjective optimization Evolutionary strategies Multi-Objective Evolutionary Algorithm Multi-objective evolutionary algorithm/D Multi-objective problem Multi-objectives optimization Multiobjective optimization problems (MOPs) Optimization algorithms Pareto solution Performance Two-stage evolution
ISSN号	09574174
DOI	10.1016/j.eswa.2021.115654
英文摘要	The balance of convergence and diversity plays a significant role to the performance of multi-objective evolutionary algorithms (MOEAs). The MOEA/D is a very popular multi-objective optimization algorithm and has been used to solve various real world problems. Like many other algorithms, the MOEA/D also has insufficient ability of convergence and diversity when tackling certain complex multi-objective optimization problems (MOPs). In this paper, a novel algorithm named MOEA/D-TS is proposed for effectively solving MOPs. The new algorithm adopts two stages evolution strategies, the first stage is focused on pushing the solutions into the area of the Pareto front and speeding up its convergence ability, after that, the second stage conducts in the operating solution's diversity and makes the solutions distributed uniformly. The performance of MOEA/D-TS is validated in the ZDT, DTLZ and IMOP problems. Compared with others popular and variants algorithms, the experimental results demonstrate that the proposed algorithm has advantage over other algorithms with regard to the convergence and diversity in most of the tested problems. © 2021 Elsevier Ltd
WOS研究方向	Computer Science ; Engineering ; Operations Research & Management Science
语种	英语
出版者	Elsevier Ltd
WOS记录号	WOS:000707414900003
内容类型	期刊论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/150779]
专题	教务处（创新创业学院）兰州理工大学国际合作处（港澳台办）
作者单位	School of Computer and Communication Technology, Lanzhou University of Technology, Lanzhou; 730050, China
推荐引用方式 GB/T 7714	Cao, Jie,Zhang, Jianlin,Zhao, Fuqing,et al. A two-stage evolutionary strategy based MOEA/D to multi-objective problems[J]. Expert Systems with Applications,2021,185.
APA	Cao, Jie,Zhang, Jianlin,Zhao, Fuqing,&Chen, Zuohan.(2021).A two-stage evolutionary strategy based MOEA/D to multi-objective problems.Expert Systems with Applications,185.
MLA	Cao, Jie,et al."A two-stage evolutionary strategy based MOEA/D to multi-objective problems".Expert Systems with Applications 185(2021).