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On the convergence analysis and parameter selection in particle swarm optimization
Abstract
A PSO with increasing inertia weight, distinct from a widely used PSO with decreasing inertia weight, is proposed in this paper. Far from drawing conclusions from sole empirical study or rule of thumb, this algorithm is derived from particle trajectory study and convergence analysis. Four standard test functions are used to confirm its validity finally. From the experiments, it is clear that a PSO with increasing inertia weight outperforms the one with decreasing inertia weight, both in convergent speed and solution precision, with no additional computing load.
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Cites
A new optimizer using particle swarm theory
Eberhart, R., & Kennedy, J. (2002) · MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science · doi:10.1109/mhs.1995.494215 · Cited by 16,067
Cited by
Particle swarm optimization: An overview
Poli, R., Kennedy, J., & Blackwell, T. (2007) · Swarm Intelligence · doi:10.1007/s11721-007-0002-0 · Cited by 21,101
Multi-Objective Particle Swarm Optimizers: A Survey of the State-of-the-Art
Coello Coello, C. A., & Reyes-Sierra, M. (2006) · International Journal of Computational Intelligence Research · doi:10.5019/j.ijcir.2006.68 · Cited by 1,365
Sengupta, S., Basak, S., & Peters, R. (2018) · Machine Learning and Knowledge Extraction · doi:10.3390/make1010010 · Cited by 543
Frankenstein's PSO: A Composite Particle Swarm Optimization Algorithm
Montes de Oca, M. A., Stutzle, T., Birattari, M., & Dorigo, M. (2009) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2009.2021465 · Cited by 366
MPSO: Modified particle swarm optimization and its applications
Tian, D., & Shi, Z. (2018) · Swarm and Evolutionary Computation · doi:10.1016/j.swevo.2018.01.011 · Cited by 363
Metadata
- Authors
- Zheng, Y.-L., Ma, L.-H., Zhang, L.-Y., & Qian, J.-X.
- Venue
- Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693)
- Publisher
- IEEE
- Published
- 2004-06-21
- Pages
- 1802-1807
- OpenAlex
- W2138273409
- Cited by
- 235
- References
- 1
- FWCI
- 8.89
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Zheng, Y.-L., Ma, L.-H., Zhang, L.-Y., & Qian, J.-X. (2004). On the convergence analysis and parameter selection in particle swarm optimization. Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693). https://doi.org/10.1109/icmlc.2003.1259789
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