人感禽流感优化算法

为求解一类复杂非线性优化问题的全局最优解,采用跨物种传播的人感禽流感传染病动力学模型提出了人感禽流感传染病优化算法。利用H7N9传染病模型构造出的S^u-S^u,I^u-I^u,S^u-I^u,I^u-S^u,S^u-D^u,I^u-D^u等算子能使个体能在同物种和跨物种个体之间充分交换信息,其中S^u-S^u、I^u-I^u算子可利用强壮个体的特征来改善虚弱个体的特征,从而提升算法的求精能力;S^u-I^u、I^u-S^u算子可改良个体的适应度分布特征,从而提升算法的探索能力;S^u-D^u,I^u-D^u算子可使极虚弱个体得到有效清除,从而降低算法陷入局部陷阱的概率。测试案例表明：本算法可快速求解一类维数较高的复杂非线性优化问题。

Optimization Algorithm Based on Human Infection with Avian Influenza

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.