SelfAdaptive-ParticleSwarmOptimization (SA-PSO)

This project implements the Self-Adaptive Particle Swarm Optimization (SA-PSO) algorithm, which combines the concepts of Particle Swarm Optimization (PSO) and Self-Adaptive mechanisms. The main feature of SA-PSO is the dynamic adaptation of the inertia weight w during the optimization process, improving the balance between exploration and exploitation.

Main Components

• Particle Class — Represents an individual particle with methods to update its velocity, position, and track the best position based on fitness.
• SAParticleSwarmOptimization Class — Manages the swarm, dynamically adjusts the inertia weight, and iteratively updates particles’ positions and velocities to find an optimal solution.

Getting Started:

To run this project, you need to install the required dependencies. You can install them using pip: 

pip install -r requirements.txt

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