Chaos-Based Adaptive Particle Swarm Optimization Implementation

This is a MATLAB program I developed implementing chaos-based adaptive particle swarm optimization. The program utilizes an emerging optimization algorithm that combines particle swarm optimization with chaotic systems. The key implementation features include adaptive parameter tuning using chaotic maps and dynamic inertia weight adjustment. The algorithm demonstrates superior convergence speed and solution accuracy compared to standard PSO variants. In my implementation, I applied this algorithm to solve complex optimization problems, achieving remarkable results that validate both the practical utility and effectiveness of the chaos-adaptive approach. The program structure includes main functions for population initialization, fitness evaluation, chaotic sequence generation, and velocity/position updates. These results provide strong evidence for the algorithm's potential in future research applications and real-world optimization scenarios.