A4 Conference proceedings

A two phase approach based on dynamic variable grouping and self-adaptive group search for large scale optimization


Open Access publication

Publication Details
Authors: Liu Haiyan, Wang Yuping, Liu Liwen, Li Xiaodong, Gao Xiao-Zhi
Publication year: 2016
Language: English
Title of parent publication: The 12th International Conference on Computational Intelligence and Security CIS 2016
Start page: 170
End page: 174
JUFO-Level of this publication: 0
Open Access: Open Access publication

Abstract
In this paper, a self-adaptive two phase approachfor large scale optimization is proposed. In the first phase, wedesign a uniform discrete search method which can quicklyand roughly scan the search space and find good initial points.Then we continuously narrow the search space and makemore precise search in a dynamically self-adaptive way. In thesecond phase, we design a dynamically self-adaptive groupingsearch scheme which can group the variables into severalgroups dynamically and assign different function evaluationsto different variable groups self-adaptively during each groupsearch. The experiment results indicate the proposed algorithmis effective and efficient.

Research Areas

Last updated on 2018-19-10 at 08:49