Abstract: To get the global optimal solution of some complex nonlinear optimization problems, an optimization algorithm based on the human avian influenza infectious diseases is proposed by using its dynamic model of cross species transmission. Applies the H7N9 infectious disease model to create the operators S^u-S^u, I^u-I^u, S^u-I^u, I^u-S^u, S^u-D^u, I^u-D^u, and to enable the individuals to exchange information among the same species and cross-species. The S^u-S^u and I^u-I^u operators can improve the characteristics of the weak individuals by that of the strong individuals, thus the exploitation ability of the algorithm can be improved. The S^u-I^u and I^u-S^u operators can improve the fitness distribution characteristics of the individuals, therefore, the exploration ability of the algorithm can be improved. The S^u-D^u and I^u-D^u operators can effectively remove the extremely weak individual, thereby the probability that the algorithm falls into a local trap can be reduced. The test cases show that the algorithm can quickly solve some complex nonlinear optimization problems with high dimensions.

Key words: swarm intelligent optimization algorithm, bin model, epidemic dynamics