基于云模型的量子免疫优化算法

采用云模型对量子免疫算法进行了改进，采用量子种群基因云对种群进化进行定性控制，基于云模型的量子旋转门自适应调整策略进行更新操作，使算法在定性知识的指导下能够自适应控制搜索空间范围，使其能在较大搜索空间条件下避开局部最优解。典型函数对比实验表明该算法可以避免陷入局部最优解，能提高全局寻优能力，能以更快的速度收敛于全局最优解，具有较好的应用价值。

Quantum immune optimization algorithm based on cloud model

A novel quantum immune optimization algorithm based on cloud model is proposed.Using quantum cloud-to-species evolution of gene populations and qualitative operation of the control and quantum based on cloud model adaptive strategy revolving door update operation,the scope of the search space can be adaptively controlled by this algorithm under the guidance of qualitative knowledge.It can avoid the local optimal solution under the conditions of the larger search space.A typical function of comparative experiment results shows that this algorithm can avoid trapping in local optimal solution,and can enhance the ability of global optimization.It can converge to the global optimal solution quickly,and has good application value.