Particle Swarm Optimization MATLAB Implementation with Detailed Code
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Resource Overview
Detailed Documentation
To facilitate better understanding of optimization algorithms, I have developed a detailed Particle Swarm Optimization (PSO) program in MATLAB. This implementation includes complete algorithmic workflow with key components: population initialization, velocity updating mechanism using cognitive and social parameters, position updates with boundary handling, and fitness evaluation. The code features adjustable parameters (swarm size, inertia weight, acceleration coefficients), convergence criteria monitoring, and visualization of optimization progress. Each function contains thorough inline comments explaining mathematical formulations and implementation logic. Example usage demonstrates parameter tuning and performance analysis for benchmark functions. This educational resource aims to support algorithm comprehension and practical application in optimization research.
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