Chaotic Particle Swarm Optimization Algorithm

This program provides a code implementation of the Chaotic Particle Swarm Optimization (CPSO) algorithm. It is designed with flexible parameters that can be modified to suit different application requirements. The algorithm simulates the collective behavior of particle swarms in nature, enhanced by chaos theory to improve global search capabilities and optimization performance. Key implementation features include particle position updates using velocity vectors, fitness evaluation functions, and chaos-based initialization for better exploration of solution spaces. Users can leverage this code to solve diverse optimization problems such as function optimization, parameter tuning, and engineering design challenges. By adjusting parameters like swarm size, inertia weight, and chaos mapping functions, the algorithm's convergence speed and solution accuracy can be further optimized. The code structure supports easy modification and extension for specialized applications, making it suitable for both research and practical implementations.