NDLI: Effect of pseudo gradient on differential evolutionary for global numerical optimization

Content Provider	IEEE Xplore Digital Library
Author	Jinliang Ding Lipeng Chen Qingguang Xie Tianyou Chai Xiuping Zheng
Copyright Year	2014
Description	Author affiliation: State Key Lab. of Synthetical Autom. for Process Ind., Northeastern Univ., Shenyang, China (Jinliang Ding; Lipeng Chen; Qingguang Xie; Tianyou Chai; Xiuping Zheng)
Abstract	In this paper, a novel pseudo gradient based DE approach is proposed, which takes advantage of both the differential evolutionary (DE) and the gradient-based algorithm. The gradient information, which is called pseudo gradient, is generated through randomly selected two vectors and their fitness function values. This work is to investigate the effect of proposed pseudo gradient on differential evolutionary algorithm. The simulation results show that DE with pseudo gradient can obtain better performance overall in comparison with classical DE variants. The pseudo gradient based DE with adaptive parameter section is compared with the existing adaptive DE algorithms. Also, the control parameter, step size are investigated to understand the mechanism of pseudo gradient in detail.
Starting Page	2019
Ending Page	2026
File Size	425019
Page Count	8
File Format	PDF
e-ISBN	9781479914883
DOI	10.1109/CEC.2014.6900463
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-07-06
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vectors Sociology Statistics Convergence Radio frequency Optimization Evolutionary computation
Content Type	Text
Resource Type	Article

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