基于Bloch球面坐标编码的量子粒子群算法及应用

Bloch Coordinates-Based Quantum Particle Swarm Optimization Algorithm and Its Application

为提高粒子群算法的优化效率,在分析粒子群优化算法的基础上,提出了一种基于Bloch球面坐标编码的量子粒子群优化算法。该算法每个粒子占据空间三个位置,每个位置代表一个优化解。采用传统粒子群优化方法的搜索机制调整量子位的两个参数,可以实现量子位在Bloch球面上的旋转,从而使每个粒子代表的三个优化解同时得到更新,并快速逼近全局最优解。标准测试函数极值优化和模糊控制其参数优化的实验结果表明,与同类算法相比,该算法在优化能力和优化效率两方面都有改进。

To improve the efficiency of particle swarm optimization, a quantum particle swarm optimization algorithm is proposed on the basis of analyzing the search process of particle swarm optimization algorithm. In the proposed algorithm, particles are endoded by qubits described on the Bloch sphere, each particle occupy three locations of the search space, and each location represents a optimization solution. By employing the search method of general PSO to adjust the two parameters of qubit, the qubits rotation are performed on the Bloch sphere, which can simultaneously update three loations occupied by a qubit and quickly approach the global optimal solution. The experimental results of standard test function extreme optimization and fuzzy controller parameters optimization show that the proposed algorithm is superior to other similar algorithm in ootimization ability and ontimization efficiency.