The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
A Cooperative Approach to Particle Swarm Optimization
Abstract
The particle swarm optimizer (PSO) is a stochastic, population-based optimization technique that can be applied to a wide range of problems, including neural network training. This paper presents a variation on the traditional PSO algorithm, called the cooperative particle swarm optimizer, or CPSO, employing cooperative behavior to significantly improve the performance of the original algorithm. This is achieved by using multiple swarms to optimize different components of the solution vector cooperatively. Application of the new PSO algorithm on several benchmark optimization problems shows a marked improvement in performance over the traditional PSO.
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Cites
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Cited by
Particle swarm optimization algorithm: An overview
Wang, D., Tan, D., & Liu, L. (2018) · Soft Computing · doi:10.1007/s00500-016-2474-6 · Cited by 3,343
Particle Swarm Optimization: A Comprehensive Survey
Shami, T. M., El-Saleh, A. A., Alswaitti, M., Al-Tashi, Q., Summakieh, M. A., & Mirjalili, S. (2022) · IEEE Access · doi:10.1109/access.2022.3142859 · Cited by 1,584
A Competitive Swarm Optimizer for Large Scale Optimization
Cheng, R., & Jin, Y. (2015) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2014.2322602 · Cited by 1,052
A social learning particle swarm optimization algorithm for scalable optimization
Cheng, R., & Jin, Y. (2015) · Information Sciences · doi:10.1016/j.ins.2014.08.039 · Cited by 747
Dynamic multi-swarm particle swarm optimizer
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Metadata
- Authors
- vandenBergh, F., & Engelbrecht, A. P.
- Venue
- IEEE Transactions on Evolutionary Computation
- Published
- 2004-06
- Volume
- 8
- Issue
- 3
- Pages
- 225-239
- ISSN
- 1089-778X (ISSN-L)
- OpenAlex
- W2118840131
- Cited by
- 2,120
- References
- 26
- FWCI
- 47.45
- Type
- journal article
- Language
- en
- Open access
- closed
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- vandenBergh, F., & Engelbrecht, A. P. (2004). A Cooperative Approach to Particle Swarm Optimization. IEEE Transactions on Evolutionary Computation. https://doi.org/10.1109/tevc.2004.826069
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