Phasor Prticle Swarm Optimization (PPSO)

Version 1.0.2 (4.99 KB) by Ebrahim Akbari

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

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Updated 19 Oct 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

Cite As

Ebrahim Akbari (2024). Phasor Prticle Swarm Optimization (PPSO) (https://www.mathworks.com/matlabcentral/fileexchange/75873-phasor-prticle-swarm-optimization-ppso), MATLAB Central File Exchange. Retrieved April 19, 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	Published	Release Notes
1.0.2	19 Oct 2021	Editing description.	Download
1.0.1	19 Oct 2021	Adding DOI to the reference paper.	Download
1.0.0	23 May 2020		Download

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}} }