一种改进型量子遗传算法

Novel Improved Quantum Genetic Algorithm

针对量子遗传算法在复杂连续函数优化中存在的收敛速度慢、易陷入局部极值等缺点,提出一种改进型量子遗传算法。采用动态策略调整量子门旋转角,以加快收敛速度,采用优体交叉策略实施交叉操作,以增强局部搜索能力。通过典型复杂连续函数的测试验证该算法的可行性和有效性。

Aiming at the shortcomings of slow convergence and easy to fall into local minimum when using Quantum Genetic Algorithm（QGA） to optimize complex continuous functions, this paper proposes a Novel Improved Quantum Genetic Algorithm（NlQGA）. It adopts the dynamic adjustment strategy to adjust the quantum rotation comer to speed up convergence rate, and uses the cross strategy of excellent individuals to get crossover operation to enhance local search ability. Test results based on typical complex continuous functions show that NIQGA is feasible and effective.