A Guaranteed Global Convergence Social Cognitive Optimizer
Joint Authors
Shu-Yan, Wang
Sun, Jia-ze
Chen, Hao
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-09-29
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
From the analysis of the traditional social cognitive optimization (SCO) in theory, we see that traditional SCO is not guaranteed to converge to the global optimization solution with probability one.
So an improved social cognitive optimizer is proposed, which is guaranteed to converge to the global optimization solution.
The global convergence of the improved SCO algorithm is guaranteed by the strategy of periodic restart in use under the conditions of participating in comparison, which helps to avoid the premature convergence.
Then we give the convergence proof for the improved SCO based on Solis and Wets’ research results.
Finally, simulation results on a set of benchmark problems show that the proposed algorithm has higher optimization efficiency, better global performance, and better stable optimization outcomes than the traditional SCO for nonlinear programming problems (NLPs).
American Psychological Association (APA)
Sun, Jia-ze& Shu-Yan, Wang& Chen, Hao. 2014. A Guaranteed Global Convergence Social Cognitive Optimizer. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-1044348
Modern Language Association (MLA)
Sun, Jia-ze…[et al.]. A Guaranteed Global Convergence Social Cognitive Optimizer. Mathematical Problems in Engineering No. 2014 (2014), pp.1-8.
https://search.emarefa.net/detail/BIM-1044348
American Medical Association (AMA)
Sun, Jia-ze& Shu-Yan, Wang& Chen, Hao. A Guaranteed Global Convergence Social Cognitive Optimizer. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-1044348
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1044348