一种改进的量子遗传算法

A Novel Improved Quantum Genetic Algorithm

针对量子遗传算法存在储存量大和易陷入局部最优解等问题,提出一种新的量子遗传算法。该算法采用角度编码方式表示染色体,从而减少编码的存储空间。引入小区间方法初始化量子种群,使量子染色体均匀分布于初值空间。利用改进的旋转门对种群进行更新操作。采用动态的量子步长调整策略实现自适应搜索。引入量子交叉和量子变异操作防止早熟问题。通过典型的多峰值函数优化实验,表明该算法具有收敛速度快、全局寻优能力强和计算时间短的特点,可以用于多峰值函数优化问题。

Aimed at the problem of large storage capacity and easily falling into local optimum,a novel improved quantum genetic algorithm is presented.The algorithm adopts an angle-coding method to reduce the storage space of chromosomes.For the quantum chromosomes are distributed averagely in space of initial value,small interval method is used to initialize quanta swarm.It uses the improved quantum rotation gates to renew the population and realizes adaptive search by the adjustment strategy of dynamic quantum step and uses the operation of quantum crossover and quantum mutation to prevent the premature problem.Through the typical multi-peak function optimization test,it shows that the algorithm has the faster convergence rate,the stronger global optimization ability and the shorter computing time.The algorithm can be used for multi-peak function optimization problem.