基于多样性变异的量子行为粒子群优化算法

为了克服量子行为的粒子群优化（QPSO）算法存在早熟收敛的缺点，本文提出了一种改进的QPSO算法，在QPSO算法中加入多样性变异算法，设置多样性函数，当多样性较少时，执行变异操作。扩大了种群搜索过程中的搜索范围，避免了种群多样性不断下降。典型标准函数优化的仿真结果表明，该算法具有较强的全局搜索能力。

Quantum-behaved particle swarm optimization with diversity-guided mutation

To overcome the premature convergence of quantum-behaved particle swarm optimization(QPSO) algorithm,this paper proposed QPSO with diversity-guided mutation(QPSO-DGM) to improve the performance of QPSO.In the proposed QPSO-DGM algorithm,set diversity function.When the value of diversity was less during the search,operated the mutation.QPSO-DGM made the particles' search scope expanded and avoided the declination of population diversity.The experiment results on benchmark functions show that both QPSO-DGM ha...