摘要
为了寻找求解大规模无约束非线性优化问题的一种有效方法,提出了一种等式约束下新的共轭梯度算法,该算法利用广义消去法将约束优化问题转化为无约束优化问题.并证明了该算法具有全局收敛性,同时还证明了该算法在强wolfe线搜索下具有充分下降性.
To search for an effective method to solve largescale unconstrained nonlinear optimization problems.In this paper,we put forward a new conjugate gradient algorithm under the equality constraints.This algorithm transforms constrained problems into unconstrained problems by generalized elimination method.We have proved that the algorithm has global convergence.At the same time,we have also proved that the algorithm has sufficient descent property in strong wolfe line search.
出处
《阜阳师范学院学报（自然科学版）》
2010年第2期16-18,35,共4页
Journal of Fuyang Normal University(Natural Science)
基金
国家自然科学基金项目(10671057)资助
关键词
等式约束
共轭梯度法
强wolfe线搜索
全局收敛性
equality constraint
conjugate gradient method
strong wolfe line search
global convergence
