Quantum-behaved particle swarm optimization with diversity-guided mutation
基于多样性变异的量子行为粒子群优化算法

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...