The K-CMA Algorithm for Solving Multi-modal Function Optimization Problems

Multi-modal function optimization must be solved when people meet with complex reality problems. With resort to the prominent search performance of CMA-ES and clustering theory, a new algorithm--K-CMA algorithm was presented. By searching local peaks and global peaks of four multi-modal functions, it can be seen from the results that this algorithm has a better result in convergence of algorithm and success rate.