一种基于免疫变异算子的改进型量子遗传算法  

An Improved Quantum Genetic Algorithm Based on Immune Mutation Operator

作　　者：陶杨[1] 韩维[1] 陶春明[2] 胡倩影[3] 

机构地区：[1]海军航空工程学院飞行器工程系,山东烟台264001 [2]安徽师范大学外国语学院,安徽芜湖241003 [3]海军装备部,北京100841

出　　处：《安徽师范大学学报（自然科学版）》2014年第3期237-241,共5页Journal of Anhui Normal University(Natural Science)

基　　金：国家自然科学基金(61032001)

摘　　要：基于量子遗传算法进化方向随机性大、易早熟等缺点提出了一种改进的量子遗传算法.该方法采用了自适应染色体长度和旋转角度,提高了优化效率;引入了免疫算子,淘汰繁殖率低的个体,并通过操作染色体编码实现量子变异,以增强种群中基因多样性,避免算法陷入局部最优.对若干基准测试函数进行实验,结果表明相对于标准量子遗传算法,该算法在收敛速度、精度、稳定性以及克服早熟能力方面都有了显著的提高.According to the disadvantages of randomness of evolutional direction and premature convergence in the Quantum Genetic Algorithm（QGA）, an improved Quantum Genetic Algorithm（IQGA） is proposed in this paper. In this method, the selfadaptive length of the chromosome and the rotation angles are adopted to increase the optimization efficiency. Based on the immune operator, the individuals owning low reproductive rates are eliminated, and the quantum mutation is achieved by chromosome coding. Thus, the gene diversity of the group is enhanced and the local optimum is avoided. By using several typical functions to examine, the simulation results show that the convergence speed, optimization precision, algorithm stability and the ability to avoid precocious phenomenon of the improved algorithm are much better than the standard one.

关 键 词：量子遗传算法 免疫算子 变异算子 自适应 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]