数学杂志Issue(1)：173-179,7.
无约束优化问题的一个下降方法
A DESCENT METHOD FOR UNCONSTRAINED OPTIMIZATION PROBLEMS
摘要
Abstract
This paper studies the unconstrained optimization problem. By using the current and previous iterative information and the curve search rule to generate a new iterative point, a new descent algorithm is proposed for solving the unconstrained optimization problem. We prove its global convergence under some mild conditions. The linear convergence rate is also proved when the objective function is uniformly convex. Numerical results show that the new method is efficient in practical computation.关键词
无约束优化/记忆梯度法/曲线搜索/收敛性Key words
unconstrained optimization/memory gradient method/curve search/conver-gence分类
数理科学引用本文复制引用
董丽,周金川..无约束优化问题的一个下降方法[J].数学杂志,2015,(1):173-179,7.基金项目
国家自然科学基金项目(11101248) （11101248）
山东省自然科学基金(ZR2010AQ026) （ZR2010AQ026）
