Phasor Prticle Swarm Optimization (PPSO)

Version 1.0.2 (4,99 KB) von Ebrahim Akbari

Phasor Prticle Swarm Optimization (PPSO) inspired from phasor theory in the mathematics.

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Aktualisiert 19. Okt 2021

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Phasor particle swarm optimization (PPSO) is a new and primary sample of PSO, based on modeling the particle control parameters with a phase angle (θ), inspired from phasor theory in the mathematics. This phase angle (θ) converts PSO algorithm to a self-adaptive, trigonometric, balanced, and nonparametric meta-heuristic algorithm. The performance of PPSO is tested on real-parameter optimization problems including unimodal and multimodal standard test functions and traditional benchmark functions.

Based on the paper:

Mojtaba Ghasemi, Ebrahim Akbari, Abolfazl Rahimnejad, Seyed Ehsan Razavi, Sahand Ghavidel, and Li Li. "Phasor particle swarm optimization: a simple and efficient variant of PSO." Soft Computing 23, no. 19 (2019): 9701-9718. DOI: https://doi.org/10.1007/s00500-018-3536-8

The full-text view-only version of the paper is available at: https://rdcu.be/720D

Zitieren als

Ebrahim Akbari (2024). Phasor Prticle Swarm Optimization (PPSO) (https://www.mathworks.com/matlabcentral/fileexchange/75873-phasor-prticle-swarm-optimization-ppso), MATLAB Central File Exchange. Abgerufen 23. Juli 2024.

Ghasemi, Mojtaba, et al. Phasor Particle Swarm Optimization: a Simple and Efficient Variant of PSO. no. 19, Springer Science and Business Media LLC, Sept. 2018, pp. 9701–18, doi:10.1007/s00500-018-3536-8.

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PPSO MATLAB Codes

Version	Veröffentlicht	Versionshinweise
1.0.2	19. Okt 2021	Editing description.	Herunterladen
1.0.1	19. Okt 2021	Adding DOI to the reference paper.	Herunterladen
1.0.0	23. Mai 2020		Herunterladen

MLA	Ghasemi, Mojtaba, et al. Phasor Particle Swarm Optimization: a Simple and Efficient Variant of PSO. no. 19, Springer Science and Business Media LLC, Sept. 2018, pp. 9701–18, doi:10.1007/s00500-018-3536-8.
APA	Ghasemi, M., Akbari, E., Rahimnejad, A., Razavi, S. E., Ghavidel, S., & Li, L. (2018). Phasor particle swarm optimization: a simple and efficient variant of PSO, 23(19), 9701–9718. Springer Science and Business Media LLC. Retrieved from https://doi.org/10.1007%2Fs00500-018-3536-8
BibTeX	@article{2018, doi = {10.1007/s00500-018-3536-8}, url = {https://doi.org/10.1007%2Fs00500-018-3536-8}, year = 2018, month = {sep}, publisher = {Springer Science and Business Media {LLC}}, volume = {23}, number = {19}, pages = {9701--9718}, author = {Mojtaba Ghasemi and Ebrahim Akbari and Abolfazl Rahimnejad and Seyed Ehsan Razavi and Sahand Ghavidel and Li Li}, title = {Phasor particle swarm optimization: a simple and efficient variant of {PSO}} }