首页|Gaussian Backbone-Based Spherical Evolutionary Algorithm with Cross-search for Engineering Problems

Gaussian Backbone-Based Spherical Evolutionary Algorithm with Cross-search for Engineering Problems

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In recent years,with the increasing demand for social production,engineering design problems have gradually become more and more complex.Many novel and well-performing meta-heuristic algorithms have been studied and developed to cope with this problem.Among them,the Spherical Evolutionary Algorithm(SE)is one of the classical representative methods that proposed in recent years with admirable optimization performance.However,it tends to stagnate prematurely to local optima in solving some specific problems.Therefore,this paper proposes an SE variant integrating the Cross-search Mutation(CSM)and Gaussian Backbone Strategy(GBS),called CGSE.In this study,the CSM can enhance its social learning ability,which strengthens the utilization rate of SE on effective information;the GBS cooperates with the original rules of SE to further improve the convergence effect of SE.To objectively demonstrate the core advantages of CGSE,this paper designs a series of global optimization experiments based on IEEE CEC2017,and CGSE is used to solve six engineering design problems with constraints.The final experimental results fully showcase that,compared with the existing well-known methods,CGSE has a very significant competitive advantage in global tasks and has certain practical value in real applications.Therefore,the proposed CGSE is a promising and first-rate algorithm with good potential strength in the field of engineering design.

Meta-heuristic algorithmsEngineering optimizationSpherical evolution algorithmGlobal optimization

Yupeng Li、Dong Zhao、Ali Asghar Heidari、Shuihua Wang、Huiling Chen、Yudong Zhang

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College of Computer Science and Technology,Changchun Normal University,Changchun 130032,Jilin,China

School of Surveying and Geospatial Engineering,College of Engineering,University of Tehran,Tehran,Iran

School of Computing and Mathematical Sciences,University of Leicester,Leicester LE1 7RH,UK

Department of Biological Sciences,Xi'an Jiaotong-Liverpool University,Suzhou 215123,Jiangsu,China

Key Laboratory of Intelligent Informatics for Safety and Emergency of Zhejiang Province,Wenzhou University,Wenzhou 325035,China

School of Computer Science and Engineering,Southeast University,Nanjing 210096,China

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MRCRoyal SocietyBHFHope Foundation for Cancer ResearchGCRFSino-UK Industrial FundLIASLIASData Science Enhancement FundFight for SightSino-UK Education FundBBSRCNatural Science Foundation of Zhejiang ProvinceNational Natural Science Foundation of China18th batch of innovative and entrepreneurial talent funding projects in Jilin ProvinceNatural Science Foundation of Jilin Province

MC_PC_17171RP202G0230AA/18/3/34220RM60G0680P202PF11RP202G0289P202ED10P202RE969P202RE23724NN201OP202006RM32G0178B8LZ22F0200056207618549YDZJ202201ZYTS567

2024

10.1007/s42235-023-00476-1

仿生工程学报(英文版)
吉林大学

仿生工程学报(英文版)

CSTPCDEI
影响因子：0.837
ISSN：1672-6529
年,卷(期)：2024.21(2)
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