基于模拟退火步长的粒子群算法

A Particle Swarm Optimization Algorithm with Simulated Annealing Step

为了提高粒子群算法的收敛速度和全局收敛性,本文在标准粒子群算法的基础上作了改进,提出了一种带模拟退火步长的粒子群算法.通过典型函数的测试结果表明新算法比原来算法收敛到最优解的次数多,提出的新算法在全局搜索能力和收敛速度方面有所提高.

In order to improve PSO convergence speed and global convergence, an advanced PSO with simulated annealing step is put forward. Typical function test results show that the new algorithm than the orig- inal algorithm converges to the optimal solution more often. The new algorithm has advantages of convergence property and speed over PSO.