概率门量子进化算法

Probability gate quantum evolution algorithm

量子进化算法(QEA)比传统进化算法(EA)有更好的种群多样性和全局寻优能力,但它采用概率操作过程,具有随机性和盲目性.将量子进化算法中的旋转门以概率门代替,在概率分析及实例验证的基础上,说明概率门量子进化算法(PGQEA)能使得对种群选取过程控制在全局优化的方向下,并且能更快地收敛于最优解.

The quantum evolutionary algorithm(QEA) has better diversity and search capacity in whole region than evolutionary algorithm(EA). For it relies on probabilistic process, it is random and blind. This paper proposes a probability gate to replace the quantum gate in QEA. The analysis bases on probability and the results of examples prove that the probability gate quantum evolution algorithm (PGQEA) can effectively control the randomicity of selecting colony from the entire territory and make them tend towards optimum individual quickly.