基于Bloch球面搜索的混沌量子免疫算法

摘要

In the existing quantum intelligent optimization algorithms, almost all of the individuals are encoded by qubits described on plane unit circle. Since there is only one adjustable parameter, quantum properties have not been fully embodied, which limits the improvement of the optimization ability further. To address this issue, a chaos quantum immune algorithm based on Bloch sphere is proposed. In the proposed algorithm, the antibodies are encoded by qubits described on Bloch sphere, the axis of rotation is designed by using Pauli matrix, the clone of the excellent antibodies is performed by rotating qubits on Bloch sphere, and the local searching is achieved by employing the chaos variables in the rotation angles. The global searching is achieved by the mutations of the inferior individuals based on the Hadamard gates. The simulation results show that the proposed algorithm is superior to other quantum intelligent optimization algorithms in both search capability and optimization efficiency.%目前大多数量子智能优化算法的个体均采用基于平面单位圆描述的量子比特编码,由于量子比特只有一个可调参数,量子特性没有得到充分体现,从而限制了优化能力的进一步提高.针对这一问题提出一种基于Bloch球面搜索的混沌量子免疫算法.该方法采用Bloch球面描述的量子比特对抗体进行编码,用泡利矩阵建立旋转轴,用量子比特在Bloch球面上的绕轴旋转实现优良抗体的克隆,通过在旋转角度中引入混沌变量动态改变转角大小实现局部搜索；用Hadamard门实现较差抗体的变异,实现全局搜索.仿真结果表明,提出的方法在搜索能力和优化效率两方面均比其他量子智能优化算法有所提高.