International Journal of Computational Intelligence Systems

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Volume 4, Issue 1, February 2011, Pages 100 - 111

Particle Swarm Optimization with Novel Processing Strategy and its Application

Authors
Yuanxia Shen, Wang, Chunmei Tap
Corresponding Author
Yuanxia Shen
Received 1 December 2009, Accepted 2 October 2010, Available Online 1 February 2011.
DOI
10.2991/ijcis.2011.4.1.9How to use a DOI?
Keywords
Particle swarm optimization; correlation coefficient; population diversity, multi-objective optimization.
Abstract

The loss of population diversity is one of main reasons which lead standard particle swarm optimization (SPSO) to suffer from the premature convergence when solving complex multimodal problems. In SPSO, the personal experience and sharing experience are processed with a completely random strategy. It is still an unsolved problem whether the completely random processing strategy is good for maintaining the population diversity. To study this problem, this paper presents a correlation PSO model in which a novel correlative strategy is used to process the personal experience and sharing experience. The relational expression between the correlation coefficient and population diversity is developed through theoretical analysis. It is found that the processing strategy with positive linear correlation is helpful to maintain the population diversity. Then a positive linear correlation PSO, PLCPSO, is proposed, where particles adopt the positive linear correlation strategy to process the personal experience and sharing experience. Finally, PLCPSO has been applied to solve single-objective and multi-objective optimization problems. The experimental results show that PLCPSO is a robust effective optimization method for complex optimization problems.

Copyright
© 2010, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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<Previous Article In Issue
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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
4 - 1
Pages
100 - 111
Publication Date
2011/02/01
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.2991/ijcis.2011.4.1.9How to use a DOI?
Copyright
© 2010, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

risenwbib
TY  - JOUR
AU  - Yuanxia Shen
AU  - Wang
AU  - Chunmei Tap
PY  - 2011
DA  - 2011/02/01
TI  - Particle Swarm Optimization with Novel Processing Strategy and its Application
JO  - International Journal of Computational Intelligence Systems
SP  - 100
EP  - 111
VL  - 4
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.2011.4.1.9
DO  - 10.2991/ijcis.2011.4.1.9
ID  - Shen2011
ER  -