Particle Swarm Optimization (PSO)

📌 Overview
This project was developed as my final research assignment for an Optimization course.
It implements the Particle Swarm Optimization (PSO) algorithm, a population-based, gradient-free optimization technique inspired by the collective behavior of bird flocks and fish schools.

The work explores:

• The theoretical foundation of PSO (inertia, cognitive/social factors)
• Its application to benchmark functions
• Parameter tuning and convergence behavior
• A Python implementation for experimentation and further research

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This repository includes:

• ParticalSwarmOptimization_4.py — a minimal PSO solver in pure Python
• Particle Swarm Optimization.docx — a short write-up explaining the algorithm, update rules, and example runs