Implementation of Particle Swarm Optimization Algorithm

This m-file implements the Particle Swarm Optimization algorithm in MATLAB environment. The objective function for PSO can be modified directly in the source code by editing the fitness function section. The implementation follows standard PSO methodology with position and velocity updates using social and cognitive components. Users can extend the file's functionality by incorporating additional features such as support for different PSO variants (e.g., inertia weight adaptation or constriction factor methods), adding more parameter tuning options for swarm size, iteration limits, or convergence criteria. The modular structure allows for easy integration of boundary handling mechanisms and parallel computation features. Through appropriate extensions and modifications, this implementation can be adapted to various optimization scenarios including constrained optimization problems and multi-objective applications, making it more flexible and practical for diverse engineering and research requirements.