A method of finding the best location in multi-dimensional space of particles is presented to achieve the optimal decision of multi-stage operation, the global convergence performance of PSO is improved by importing a cross operator of GA and using a self
A method of finding the best location in multi-dimensional space of particles is presented to achieve the optimal decision of multi-stage operation, the global convergence performance of PSO is improved by importing a cross operator of GA and using a self
提出以确定微粒群在多维空间中的最优位置来实现多阶段优化调度决策的方法，并针对算法易陷入局部最优的缺陷，引入遗传算法中的“杂交”因子以及采用自适应的惯性权重，以改进其全局优化能力。