一种新的非线性共轭梯度法的全局收敛性

The Global Convergence of a New Nonlinear Conjugate Gradient Method

给出了一种新的求解非线性无约束优化问题的共轭梯度法,我们证明了该方法对相应的算法具有全局收敛性,同时我们还证明了该方法在强Wolfe线搜索下具有充分下降性.并且本算法给出了比较好的数值结果.

In this paper,we present a new conjugate gradient method for unconstrained optimization based on Fletcher-Reeves algorithms and proved that with the strong Wolfe line search the new method can support the global convergence result. At the same time, the new conjugate gradient algorithm satisfies the sufficient descent property. We also obtainded better numerical results by this algorithm.