关键词: 粒子群优化, 变异, 自适应调整, 优化算法

Abstract: In order to enhance the optimization efficiency of quantum particle swarm optimization coding based on the probability amplitude，an improved quantum particle swarm optimization is proposed.In the proposed algorithm，the mutation of particle position is performed by quantum Hadamard-gate，the exchange mutation of probability amplitude is improved into the rotation adjustment with better flexibility，and this avoids the loss of population diversity in search space.By studying the relationship among inertia factors，self-factors and global-factors，an adaptive determination method of the global-factors according to the current fitness is proposed.With application of function extremum optimization，the simulation results show that the proposed algorithm is superior to the original one in both search capability and optimization efficiency.

Key words: particle swarm optimization, mutation, adaptive adjustment, optimization algorithm