Particle Swarm Optimization (Vectorized Code)

a simple implementation of Particle Swarm Optimization algorithm (PSO)
Updated 17 Jun 2014

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Particle swarm optimization (PSO) is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. PSO optimizes a problem by having a population of candidate solutions, here dubbed particles, and moving these particles around in the search-space according to simple mathematical formulae over the particle's position and velocity. Each particle's movement is influenced by its local best known position but, is also guided toward the best known positions in the search-space, which are updated as better positions are found by other particles. This is expected to move the swarm toward the best solutions.
This code is based on the original PSO code in "file exchange" by Wesam Elshamy.

Cite As

Reza Ahmadzadeh (2024). Particle Swarm Optimization (Vectorized Code) (, MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2010a
Compatible with any release
Platform Compatibility
Windows macOS Linux

Inspired by: Particle Swarm Optimization Simulation

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