题名 | Adaptive multiobjective evolutionary algorithm for large-scale transformer ratio error estimation |
作者 | |
通讯作者 | He, Cheng |
发表日期 | 2022-05-01
|
DOI | |
发表期刊 | |
ISSN | 1865-9284
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EISSN | 1865-9292
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卷号 | 14页码:237-251 |
摘要 | As a typical large-scale multiobjective optimization problem extracted from real-world applications, the voltage transformer ratio error estimation (TREE) problem is challenging for existing evolutionary algorithms (EAs). Due to the large number of decision variables in the problems, existing algorithms cannot solve TREE problems efficiently. Besides, most EAs may fail to balance the convergence enhancement and diversity maintenance, leading to the trap in local optima even at the early stage of the evolution. This work proposes an adaptive large-scale multiobjective EA (LSMOEA) to handle the TREE problems with thousands of decision variables. Generally, multiple efficient offspring generation and environmental selection strategies selected from some representative LSMOEAs are included. Then an adaptive selection strategy is used to determine which offspring generation and environmental selection operators are used in each generation of the evolution. Thus, the search behavior of the proposed algorithm evolves along with the evolution process, the balance between convergence and diversity is maintained, and the proposed algorithm is expected to solve TREE problems effectively and efficiently. Experimental results show that the proposed algorithm achieves significant performance improvement due to the adaptive selection of different operators, providing an effective and efficient approach for large-scale optimization problems. |
关键词 | |
相关链接 | [来源记录] |
收录类别 | |
语种 | 英语
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学校署名 | 第一
; 通讯
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资助项目 | National Natural Science Foundation of China["U20A20306",61903178,61906081]
; Guangdong Basic and Applied Basic Research Foundation[2019A1515110575]
; Guangdong Provincial Key Laboratory[2020B121201001]
; Program for Guangdong Introducing Innovative and Enterpreneurial Teams[2017ZT07X386]
; Shenzhen Science and Technology Program["KQTD2016112514355531","RCBS20200714114817264"]
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WOS研究方向 | Computer Science
; Operations Research & Management Science
|
WOS类目 | Computer Science, Artificial Intelligence
; Operations Research & Management Science
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WOS记录号 | WOS:000790694500001
|
出版者 | |
EI入藏号 | 20221912094186
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EI主题词 | Decision making
; Errors
; Evolutionary algorithms
; Forestry
; Power transformers
; Trees (mathematics)
|
EI分类号 | Electric Power Lines and Equipment:706.2
; Woodlands and Forestry:821.0
; Management:912.2
; Combinatorial Mathematics, Includes Graph Theory, Set Theory:921.4
; Optimization Techniques:921.5
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来源库 | Web of Science
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引用统计 |
被引频次[WOS]:4
|
成果类型 | 期刊论文 |
条目标识符 | http://sustech.caswiz.com/handle/2SGJ60CL/334346 |
专题 | 工学院_计算机科学与工程系 |
作者单位 | 1.Southern Univ Sci & Technol, Dept Comp Sci & Engn, Guangdong Prov Key Lab Brain Inspired Intelligent, Shenzhen 518055, Peoples R China 2.Huazhong Univ Sci & Technol, Sch Artificial Intelligence & Automat, Key Lab Image Informat Proc & Intelligent Control, Wuhan 430074, Peoples R China |
第一作者单位 | 计算机科学与工程系 |
通讯作者单位 | 计算机科学与工程系 |
第一作者的第一单位 | 计算机科学与工程系 |
推荐引用方式 GB/T 7714 |
Huang, Changwu,Li, Lianghao,He, Cheng,et al. Adaptive multiobjective evolutionary algorithm for large-scale transformer ratio error estimation[J]. Memetic Computing,2022,14:237-251.
|
APA |
Huang, Changwu,Li, Lianghao,He, Cheng,Cheng, Ran,&Yao, Xin.(2022).Adaptive multiobjective evolutionary algorithm for large-scale transformer ratio error estimation.Memetic Computing,14,237-251.
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MLA |
Huang, Changwu,et al."Adaptive multiobjective evolutionary algorithm for large-scale transformer ratio error estimation".Memetic Computing 14(2022):237-251.
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条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | 操作 | |
Adaptive multiobject(1172KB) | 期刊论文 | 作者接受稿 | 限制开放 | CC BY-NC-SA |
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