MECSBO: Multi-strategy enhanced circulatory system based optimisation algorithm for global optimisation and reliability-based design optimisation problems

IF 2.5 Q2 ENGINEERING, INDUSTRIAL
Shiyuan Yang, Chenhao Guo, Debiao Meng, Yipeng Guo, Yongqiang Guo, Lidong Pan, Shun-Peng Zhu
{"title":"MECSBO: Multi-strategy enhanced circulatory system based optimisation algorithm for global optimisation and reliability-based design optimisation problems","authors":"Shiyuan Yang,&nbsp;Chenhao Guo,&nbsp;Debiao Meng,&nbsp;Yipeng Guo,&nbsp;Yongqiang Guo,&nbsp;Lidong Pan,&nbsp;Shun-Peng Zhu","doi":"10.1049/cim2.12097","DOIUrl":null,"url":null,"abstract":"<p>The Circulatory System Based Optimisation (CSBO) stands as a nascent metaheuristic optimisation algorithm known for its proficiency in tackling global optimisation problems. The authors introduce the Multi-strategy Enhanced CSBO (MECSBO), an algorithm designed for global optimisation and Reliability-based Design Optimisation (RBDO). MECSBO integrates adaptive inertia weight, golden sine operator and chaos strategy to augment the convergence capacity and efficiency of the original CSBO. Furthermore, MECSBO-based RBDO algorithm is presented to address RBDO problem. The comparative analysis utilising standard real-world benchmark functions has been carried out to validate the effectiveness of the proposed MECSBO. Several RBDO problems, including three typical numerical examples and three engineering cases, are used to show abilities of the proposed MECSBO-based RBDO algorithm. The results demonstrated that MECSBO is outperformed comparing to the state-of-the-art algorithms in terms of accuracy, efficiency, and robustness in RBDO problems.</p>","PeriodicalId":33286,"journal":{"name":"IET Collaborative Intelligent Manufacturing","volume":"6 2","pages":""},"PeriodicalIF":2.5000,"publicationDate":"2024-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cim2.12097","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Collaborative Intelligent Manufacturing","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/cim2.12097","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 0

Abstract

The Circulatory System Based Optimisation (CSBO) stands as a nascent metaheuristic optimisation algorithm known for its proficiency in tackling global optimisation problems. The authors introduce the Multi-strategy Enhanced CSBO (MECSBO), an algorithm designed for global optimisation and Reliability-based Design Optimisation (RBDO). MECSBO integrates adaptive inertia weight, golden sine operator and chaos strategy to augment the convergence capacity and efficiency of the original CSBO. Furthermore, MECSBO-based RBDO algorithm is presented to address RBDO problem. The comparative analysis utilising standard real-world benchmark functions has been carried out to validate the effectiveness of the proposed MECSBO. Several RBDO problems, including three typical numerical examples and three engineering cases, are used to show abilities of the proposed MECSBO-based RBDO algorithm. The results demonstrated that MECSBO is outperformed comparing to the state-of-the-art algorithms in terms of accuracy, efficiency, and robustness in RBDO problems.

Abstract Image

MECSBO:基于多策略增强循环系统的优化算法,用于全局优化和基于可靠性的设计优化问题
基于循环系统的优化(CSBO)是一种新兴的元启发式优化算法,以其在解决全局优化问题方面的熟练程度而闻名。作者介绍了多策略增强 CSBO(MECSBO),这是一种专为全局优化和基于可靠性的设计优化(RBDO)而设计的算法。MECSBO 整合了自适应惯性权重、黄金正弦算子和混沌策略,以增强原始 CSBO 的收敛能力和效率。此外,还提出了基于 MECSBO 的 RBDO 算法来解决 RBDO 问题。利用标准实际基准函数进行了比较分析,以验证所提出的 MECSBO 的有效性。通过几个 RBDO 问题,包括三个典型的数值示例和三个工程案例,展示了所提出的基于 MECSBO 的 RBDO 算法的能力。结果表明,在 RBDO 问题中,MECSBO 在准确性、效率和鲁棒性方面都优于最先进的算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
IET Collaborative Intelligent Manufacturing
IET Collaborative Intelligent Manufacturing Engineering-Industrial and Manufacturing Engineering
CiteScore
9.10
自引率
2.40%
发文量
25
审稿时长
20 weeks
期刊介绍: IET Collaborative Intelligent Manufacturing is a Gold Open Access journal that focuses on the development of efficient and adaptive production and distribution systems. It aims to meet the ever-changing market demands by publishing original research on methodologies and techniques for the application of intelligence, data science, and emerging information and communication technologies in various aspects of manufacturing, such as design, modeling, simulation, planning, and optimization of products, processes, production, and assembly. The journal is indexed in COMPENDEX (Elsevier), Directory of Open Access Journals (DOAJ), Emerging Sources Citation Index (Clarivate Analytics), INSPEC (IET), SCOPUS (Elsevier) and Web of Science (Clarivate Analytics).
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信