Global optimization with the PSO coupling-type discrete gradient chaos model

In this paper, we propose a new multiagent discrete gradient chaos model using a coupling structure which PSO has. Concretely, first, we introduce a multiagent-type optimization model whose agents search autonomously with the discrete gradient chaos model which is the simplest dynamical global search model, and they are coupled by convective coupling. Convective coupling in this model is used to aim at overcoming of emergence of boundary crisis which is a problem of the original discrete gradient chaos model. Second, we introduce PSO coupling structure, where population drifts to the gbest and the pbest, into discrete gradient chaos model. Then, we propose "PSO coupling-type discrete gradient chaos model" with the search strategy based on objective function's value. In this paper, our proposed models are applied to several benchmark problems. The results show that our proposed models have better global optimization ability than the original discrete gradient chaos model and PSO model.