| 一类新的曲线搜索下的多步下降算法 |
| |
| 引用本文： | 汤京永,董丽,李学志.一类新的曲线搜索下的多步下降算法[J].应用数学,2009,22(4). |
| |
| 作者姓名： | 汤京永 董丽 李学志 |
| |
| 作者单位： | 1. 上海交通大学数学系,上海,200240;信阳师范学院数学与信息科学学院,河南,信阳,464000
2. 信阳师范学院数学与信息科学学院,河南,信阳,464000 |
| |
| 基金项目： | 国家自然科学基金项目 |
| |
| 摘 要： | 提出一类新的曲线搜索下的多步下降算法,在较弱条件下证明了算法具有全局收敛性和线性收敛速率.算法利用前面多步迭代点的信息和曲线搜索技巧产生新的迭代点,收敛稳定,不用计算和存储矩阵,适于求解大规模优化问题.数值试验表明算法是有效的.
|
| 关 键 词： | 无约束优化 曲线搜索 全局收敛性 线性收敛速率 |
A New Class of Multi-step Descent Methods with Curve Search Rule |
| |
| TANG Jing-yong,DONG Li,LI Xue-zhi.A New Class of Multi-step Descent Methods with Curve Search Rule[J].Mathematica Applicata,2009,22(4). |
| |
| Authors: | TANG Jing-yong DONG Li LI Xue-zhi |
| |
| Abstract: | This paper presents a new class of multi-step descent methods with curve search rule. We prove its global convergence and linear convergence rate under some mild conditions. The methods use previous multi-step iterative information and curve search rule to generate new iterative points at each iteration. This makes the new method converge stably and be more suitable to solve large scale optimization problems by avoiding the computation and storage of some matrices. Numerical experiments show that the new method is available and efficient in practical computation. |
| |
| Keywords: | Unconstrained optimizations Curve search rule Global convergence Linear convergence rate |
| 本文献已被 万方数据 等数据库收录！ |
|
