Particle Swarm Optimization with Novel Processing Strategy and its Application
- 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/).
Cite this article
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 -