An Bio-inspired Complex System Dynamic Optimization Decision Method

through the observation and study of social creatures, biologists and computing experts proposed many bio-inspired optimization algorithm based on simulated biological behavior. These algorithms show strong vitality and potential of further development in solving traditional NP and practical complex optimization problem. But most existing research results mainly focused on the use of biological behavior phenotypic mechanism to achieve the function optimization and engineering control, but the analysis of internal control mechanisms of biological behavior is not sufficient, it needs further research. Based on complex system dynamics model, this paper proposes a bio-inspired dynamics optimization decision method. This method combines the swarm dynamics model, population logistic growth model and three evolve elements. Based on the test of constrained optimization problems, experiment results indicate that this method is effective. Finally, conclusion and the further work are given.