求解无约束优化问题的一种新的共轭梯度法

A New Conjugate Gradient Method for Solving Unconstrained Optimization Problems

一般情况下,求解大规模约束问题的有效算法是共轭梯度法,βk的选取不同构成不同的共轭梯度法。提出了求解无约束优化问题的一种新的共轭梯度法,修正了βk,并在Wolfe线搜索下证明了它的全局收敛性。

In the ordinary circumstances,conjugate gradient method was an effective algorithm for solving large-scale restraint problems,different selections constructed different conjugate gradient methods.A new conjugate gradient method is proposed for solving unconstrained optimization problems to update and prove the method with Wolfe line search convergece globally.