A new hybrid Particle Swarm Optimization with wavelet theory based mutation operation
Sai Ho Ling, C.W. Yeung, K.Y. Chan, Herbert Ho‐Ching Iu, Frank H. F. Leung · 2007
An improved hybrid particle swarm optimization (PSO) that incorporates a wavelet-based mutation operation is proposed It applies wavelet theory to enhance PSO in exploring solution spaces more effectively for better solutions. A suite of benchmark test functions and an application example on tuning an associative-memory neural network are employed to evaluate the performance of the proposed method. It is shown empirically that the proposed method outperforms significantly the existing methods in terms of convergence speed, solution quality and solution stability.