A novel hybrid combination optimization algorithm based on search area segmentation and fast Fourier transform

doi:10.1080/0305215X.2018.1502759

	A novel hybrid combination optimization algorithm based on search area segmentation and fast Fourier transform
	Zhao, Fuqing 4; Yang, Guoqiang 4; Zhang, Yi 1; Lei, Wenchang 4; Ma, Weimin 2; Zhang, Chuck 3
刊名	Engineering Optimization
	2019-05-04
卷号	51 期号:5 页码:846-861
关键词	Benchmarking Global optimization Gradient methods Binary search Global optimization problems Gradient descent Gradient descent algorithms Hybrid optimization algorithm Numerical optimizations Search area State-of-the-art algorithms
ISSN号	0305215X
DOI	10.1080/0305215X.2018.1502759
英文摘要	A novel hybrid optimization algorithm combining search area segmentation technique and the fast Fourier transform (HSAS/FFT) is presented to solve the numerical optimization problems. Firstly, the spectrum of each dimension of the objective function can be acquired by the FFT. The search space is segmented by using the spectrum to ensure that each subspace is unimodal. Secondly, the population of subspaces is produced and the optimal individual can be obtained by gradient descent algorithm. Finally, the local optimal solution in the optimal subspace is generated by the binary search algorithm. Make the optimal individual the new search space and repeat the process until meeting the termination condition. The proposed HSAS/FFT was tested on the CEC2017 benchmark, which evaluates the performance of the proposed algorithm on solving global optimization problems. Results obtained show that HSAS/FFT has an excellent performance and better convergence speed in comparison with some of the state-of-the-art algorithms. © 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.
WOS研究方向	Engineering ; Operations Research & Management Science
语种	英语
出版者	Taylor and Francis Ltd.
WOS记录号	WOS:000460643500007
内容类型	期刊论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/150638]
专题	国际合作处（港澳台办）
作者单位	1.School of Mechanical Engineering, Xijin University, Xi’an, China; 2.School of Economics and Management, Tongji University, Shanghai, China; 3.H. Milton Stewart School of Industrial & Systems Engineering, Georgia Institute of Technology, Atlanta, United States 4.School of Computer and Communication Technology, Lanzhou University of Technology, Lanzhou, China;
推荐引用方式 GB/T 7714	Zhao, Fuqing,Yang, Guoqiang,Zhang, Yi,et al. A novel hybrid combination optimization algorithm based on search area segmentation and fast Fourier transform[J]. Engineering Optimization,2019,51(5):846-861.
APA	Zhao, Fuqing,Yang, Guoqiang,Zhang, Yi,Lei, Wenchang,Ma, Weimin,&Zhang, Chuck.(2019).A novel hybrid combination optimization algorithm based on search area segmentation and fast Fourier transform.Engineering Optimization,51(5),846-861.
MLA	Zhao, Fuqing,et al."A novel hybrid combination optimization algorithm based on search area segmentation and fast Fourier transform".Engineering Optimization 51.5(2019):846-861.