A Hybrid Evolution Algorithm with Application Based on Chaos Genetic Algorithm and Particle Swarm Optimization

摘要

Aiming at the complex function extreme value and non-linear system model parameters adjust, a hybrid optimization algorithm based on chaos GA combined with PSO is proposed in the paper. With application of applying experience of PSO, sharing information of GA, and traversing pathway of chaos, the adaptive switching of two algorithms are implemented through estimating the fitness and optimization efficiency, which may quickly obtain the global optimal solution. The proposed algorithm is applied to the function extreme optimizing and the parameter adjusting of fuzzy controller, and the experimental results show that the optimization ability of proposed algorithm is obviously superior to the single one, and that the integration of some intelligent optimization algorithms is a potential research direction.