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A co-evolutionary particle swarm optimization with dynamic topology for solving multi-objective optimization problems

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成果类型:
期刊论文
作者:
Wu, Daqing;Tang, Lixiang;Li, Haiyan;Ouyang, LiJun
通讯作者:
Tang, Lixiang(Tanglx0731@126.com)
作者机构:
[Li, Haiyan; Ouyang, LiJun; Wu, Daqing] Computer Science and Technology Institute, University of South China, Hangyang, Hunan, China
[Tang, Lixiang] Department of Business Administration, Hunan University of Finance and Economics, Hunan, 410205, China
[Wu, Daqing] Key Laboratory of Intelligent Computing and Signal Processing, Ministry of Education, Anhui University, Hefei, Anhui Province, 230039, China
[Wu, Daqing] Key Laboratory of Guangxi High Schools for Complex System and Computational Intelligence, Guangxi University for Nationalities, Nanning, 530006, China
[Wu, Daqing] Artificial Intelligence Key Laboratory of Sichuan Province (Sichuan University of Science and Engineering), Zigong, 643000, China
通讯机构:
[Tang, L.] D
Department of Business Administration, China
语种:
英文
关键词:
Diversity;Multi-objective optimization;Particle swarm optimizer;Two local best solutions
期刊:
Advances in modelling and analysis. A, general mathematical and computer tools
ISSN:
1258-5769
年:
2016
卷:
53
期:
1
页码:
145-159
机构署名:
本校为第一机构
院系归属:
计算机科学与技术学院
摘要:
This paper proposes a multi-objective with dynamic topology particle swarm optimization (PSO) algorithm for solving multi-objective problems, named DTPSO. One of the main drawbacks of classical multi-objective particle swarm optimization algorithm is low diversity. To overcome this disadvantage, DTPSO uses two dynamic local best particles to lead the search particles with multiple populations to deal with multiple objectives, and maintains diversity of new found non-dominated solutions via partitioned the searching space into fixed number of cells. The proposed DTPSO is validated through compa...

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