一种基于Cauchy变异的量子粒子群算法

摘要

Comparing with the other optimization algorithms, particle swarm optimization (PSO)has the merits of fast convergence rata and easy application, but the results of research have shown that the PSO has the shortcoming that it is easily be trapped into local optimum. A quantum-behaved particle swarm optimization with Cauchy mutation (CQPSO) is presented. The results of experiment show that the new algorithm not only accelerate the global search ability but also accelerate the convergence rate of the PSO, so it can be applied in engineering optimization problems.%和其他优化算法相比，粒子群算法有着简单易实现以及寻优结果快的优点，但研究结果表明标准粒子群算法在优化过程中存在着易于陷入最小的缺陷。文章提出了一种基于Cauchy策略的量子-粒子群算法。标准测试函数的仿真结果表明，新的算法不仅能够提高算法的全局搜索能力，而且能够加快算法的寻优速度，能够应用在实际工程中的函数优化问题。