摘要
研究利用共轭梯度法求解无约束最优化问题。为了保证共轭梯度方向是目标函数的充分下降方向,对共轭梯度算法中的共轭梯度方向参数确定了一个取值范围并与W olfe步长搜索相结合,提出了新的共轭梯度算法,使算法具有更好的收敛速度,特别是在求解大规模无约束最优化问题时,此算法只需要较小的存储。
Conjugate gradient optimization algorithms depend on the search directions with different choice for the parameter in the conjugate gradient directions. In this paper, conditions are given on the parameter to ensure that the conjugate direction is sufficient descent, and a new conjugate gradient method is proposed. This algorithm only needs a smaller memory and has the better convergence rate.
出处
《太原科技大学学报》
2009年第3期251-253,共3页
Journal of Taiyuan University of Science and Technology