基于多链拓展编码方案的量子遗传算法

为了提高量子遗传算法的性能,提出了一种基于多链拓展编码方案的量子遗传算法。根据编码方案,将每个量子位分解为多个并列的基因,有效地拓展了搜索空间;结合编码方案提出量子更新策略,并引入了动态调整旋转角机制对个体进行更新,使用量子非门变异策略实现量子变异。仿真实验中,分析了使用不同变异概率[0,0.1,…,0.9,1]时对算法性能的影响,对比了分别使用普通量子遗传算法、双链编码方案、三链编码方案以及四链编码方案的量子遗传算法在优化函数极值问题时算法的性能。实验结果证明,通过增加基因链可以显著提高算法的性能,多链拓展编码方案可以提高量子遗传算法的性能,是有效的。

Quantum genetic algorithm based on multi-chain coding scheme

In order to improve the efficiency of the quantum genetic algorithm,this paper proposed a quantum genetic algorithm based on a expanded multi-chain coding scheme.The algorithm took qubit as chromosome.Each chromosome generated multiple and parallel gene chains which were mapping to multiple optimized solutions by separating qubit into multiple and parallel genes.The expanded genes chains expanded the searching space effectively and increased evolutionary rate for quantum genetic algorithm.It introduced the dynamic adjusting rotation angle mechanism to quantum rotation gate to guide individual evolution and used quantum not-gate to prevent algorithm occurring premature convergence.The method further improved searching efficiency.In the simulation experiment,analysed the influence for the algorithm with different variation probability([0,0.1,…,0.9,1])and used different code schemes to optimize extremal function.The simulation experiment result shows that it can obviously improve the efficiency of quantum genetic algorithm by adding gene chain,and the quantum genetic algorithm based on a expanded multi-chain coding scheme is efficient.