【摘要】 文章运用分组粒子群的方法来解决非线性约束规划问题,将粒子群分成几个小组分别进化,几个小组的参数各自随机产生。在一定的间隔时刻对各个小组的粒子进行重新分组和参数的调整,并根据收敛性检查的情况将劣质粒子淘汰重新初始化,这不仅有助于在不同环境进化出的粒子相互取长补短,而且可以有效的防止陷入局部最优。更多还原

【Abstract】 A grouping particle swarm optimization approach is presented to solve the nonlinear constrained optimization problems.It divides the particle swarm into several small groups,each group will have its own evolution parameters.It will optimize parameters after some evolution time and redivide the particle swarm,and it will initialize the bad particle if convergence is too early to find.The grouping PSO gets more efficiency converge speed and the convenient of operation.更多还原