摘要
结合复形法与粒子群算法的优点,提出粒子群复形法,用于求解非线性方程组,以克服牛顿法初始点不易选择的问题,同时克服复形法与粒子群算法由于易陷入局部极值而导致方程组的解的精度不够的不足.数值计算结果表明此方法具有全局搜索性,特别是,它能够以满意的精度求出对未知数具有敏感性的非线性方程组的解.
A complex particle swarm optimization （CPSO） algorithm, which combines the advantages of method of complex （MC） and particle swarm optimization （PSO）, is put forward to solve systems of nonlinear equations, and it can be used to overcome the difficulty in selecting good initial guess for Newton＇s method and the inaccuracy of MC and PSO due to being easily trapped into local minima for solving systems of nonlinear equations. Numerical computations show that the approach has global searching capability and can give satisfactory solutions, especially for the system of nonlinear equations, which is sensitive to the variables.
出处
《信息与控制》
CSCD
北大核心
2006年第4期423-427,共5页
Information and Control
基金
国家自然科学基金资助项目(20276063)
关键词
非线性方程组
复形法
粒子群算法
system of nonlinear equations
method of complex （MC）
particle swarm optimization （PSO）
