摘要
并行文化微粒群优化算法是一种改进的微粒群优化算法,具有较强的全局搜索能力。将非线性方程组的求解问题转化为函数优化问题,应用并行文化微粒群优化算法求解非线性方程组的解。计算中不需要使用目标函数的导数信息和初始点信息,数值实验结果表明了该算法的有效性和可行性。
Parallel Particle Swarm Optimization based on Cultural Algorithm （CA-PSO） is an improved particle swarm optimization algorithm, which has strong global search ability. The problem of solving nonlinear equation and system problems is transferred to the problem of function optimization, and the CA-PSO is ap- plied to solving the problem. The derivative of objective function and initial point of information is not used in the computation. Numerical results show that the algorithm is feasible and effective.
出处
《科技广场》
2010年第5期27-29,共3页
Science Mosaic
关键词
微粒群优化算法
文化算法
非线性方程组
函数优化
Particle Swarm Optimization
Culture Algorithm
Nonlinear System
Function Optimization
