Lanzhou University of Technology Institutional Repository (LUT_IR)
Elitist Guided Parameter Adaptive Brain Storm Optimization Algorithm | |
Zhao, Fuqing; Hu, Xiaotong; Zhao, Jinlong; Liu, Huan | |
2021 | |
会议名称 | 24th IEEE International Conference on Computer Supported Cooperative Work in Design (IEEE CSCWD) |
会议录名称 | PROCEEDINGS OF THE 2021 IEEE 24TH INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK IN DESIGN (CSCWD) |
页码 | 679-683 |
会议日期 | MAY 05-07, 2021 |
会议地点 | Dalian, PEOPLES R CHINA |
出版地 | NEW YORK |
出版者 | IEEE |
摘要 | With the increasing complexity of continuous optimization problems, the requirement of solving algorithms is higher and higher. To improve the performance of brain storm optimization algorithm, an elitist guided parameter adaptive BSO (EGBSO) is proposed in this paper. The population is sorted in the objective space based on the fitness. The top M individuals are regarded as elitists to guide the ordinary individuals to cluster, which accelerates the convergence speed of the algorithm. The updating mechanism of elite guidance is introduced, which utilizes the cooperation between global optimal individual and elitists to guide the population to a better direction. An adaptive selection parameter is set to make the algorithm more inclined to global search in the early stage and local search in the later stage, balancing the exploration and exploitation capabilities. The proposed EGBSO algorithm and three comparison algorithms are tested on the CEC2017 benchmark test suit, and the experimental results show that the EGBSO has good performance in solving complex optimization problems. |
关键词 | brain storm optimization elitist guidance cooperation parameter adaptive |
DOI | 10.1109/CSCWD49262.2021.9437860 |
收录类别 | CPCI-S |
语种 | 英语 |
WOS记录号 | WOS:000716858200116 |
引用统计 | |
文献类型 | 会议论文 |
条目标识符 | https://ir.lut.edu.cn/handle/2XXMBERH/150135 |
专题 | 国际合作处(港澳台办) |
通讯作者 | Zhao, Fuqing |
作者单位 | Lanzhou Univ Technol, Sch Comp & Commun Technol, Lanzhou, Peoples R China |
第一作者单位 | 兰州理工大学 |
通讯作者单位 | 兰州理工大学 |
推荐引用方式 GB/T 7714 | Zhao, Fuqing,Hu, Xiaotong,Zhao, Jinlong,et al. Elitist Guided Parameter Adaptive Brain Storm Optimization Algorithm[C]. NEW YORK:IEEE,2021:679-683. |
条目包含的文件 | 条目无相关文件。 |
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