一种求解高校路网的逆序变异的新混合PSO算法

摘要

Standard Particle Swarm Optimization(SPSO) easily leads to premature convergence in optimizing path problem. To o-vercome this shortcoming and according to university geographic coordinates, a new hybrid PSO algorithm of inverted sequence variation is proposed for solving university path problem. To balance the ability of local search and global search of PSO and enhance the population diversity, variation condition is a self-balancing strategy. According to the reverse mutation rate operator, new groups start to do position variation for the particles to get rid of local minima and continue iterative update operation. The C ++ programming of Visual Studio 2005 is used to make simulation. The results show that this algorithm can not only effectively solve the university path problem, but also is of high convergence precision and overcomes premature convergence effectively.%针对标准粒子群算法在求解路网问题时显现出易陷入局部极值的问题,根据高校地理数据,提出一种求解高校路网的逆序变异的新混合PSO算法.为平衡算法的全局和局部搜索能力及增强种群多样性,将一种自平衡策略作为变异条件,在产生新的群体中按照逆序变异率算子对粒子进行位置变异,从而使得粒子摆脱局部极值后继续进行迭代更新操作.以Visual Studio 2005中C++编程实现实验仿真,结果表明此算法不但能有效求解高校路网问题,而且新算法收敛精度高,有效克服了早熟收敛问题.