The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
Cooperatively Coevolving Particle Swarms for Large Scale Optimization
Open accessAbstract
This paper presents a new cooperative coevolving particle swarm optimization (CCPSO) algorithm in an attempt to address the issue of scaling up particle swarm optimization (PSO) algorithms in solving large-scale optimization problems (up to 2000 real-valued variables). The proposed CCPSO2 builds on the success of an early CCPSO that employs an effective variable grouping technique random grouping. CCPSO2 adopts a new PSO position update rule that relies on Cauchy and Gaussian distributions to sample new points in the search space, and a scheme to dynamically determine the coevolving subcomponent sizes of the variables. On high-dimensional problems (ranging from 100 to 2000 variables), the performance of CCPSO2 compared favorably against a state-of-the-art evolutionary algorithm sep-CMA-ES, two existing PSO algorithms, and a cooperative coevolving differential evolution algorithm. In particular, CCPSO2 performed significantly better than sep-CMA-ES and two existing PSO algorithms on more complex multimodal problems (which more closely resemble real-world problems), though not as well as the existing algorithms on unimodal functions. Our experimental results and analysis suggest that CCPSO2 is a highly competitive optimization algorithm for solving large-scale and complex multimodal optimization problems.
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Cites
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Self-citationA Cooperative Approach to Particle Swarm Optimization
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Data-intensive applications, challenges, techniques and technologies: A survey on Big Data
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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
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Major Advances in Particle Swarm Optimization: Theory, Analysis, and Application
Houssein, E. H., Gad, A. G., Hussain, K., & Suganthan, P. N. (2021) · Swarm and Evolutionary Computation · doi:10.1016/j.swevo.2021.100868 · Cited by 466
RetractedBig data: From beginning to future
Yaqoob, I., Hashem, I. A. T., Gani, A., Mokhtar, S., Ahmed, E., Anuar, N. B., & Vasilakos, A. V. (2016) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2016.07.009 · Cited by 410
Metadata
- Authors
- Li, X., & Yao, X.
- Venue
- IEEE Transactions on Evolutionary Computation
- Published
- 2012-04
- Volume
- 16
- Issue
- 2
- Pages
- 210-224
- ISSN
- 1089-778X (ISSN-L)
- 1941-0026
- OpenAlex
- W2155005783
- Cited by
- 745
- References
- 27
- FWCI
- 39.32
- Type
- journal article
- Language
- en
- Open access
- green
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