Phasor Prticle Swarm Optimization (PPSO)

Phasor Prticle Swarm Optimization (PPSO) inspired from phasor theory in the mathematics.
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Mise à jour 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:
The full-text view-only version of the paper is available at:

Citation pour cette source

Ebrahim Akbari (2024). Phasor Prticle Swarm Optimization (PPSO) (, MATLAB Central File Exchange. Récupéré le .

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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