期刊文献+

无约束极值问题的拟合方法(英文) 被引量:1

A Fitting Method for Unconstrained Minimizations
下载PDF
导出
摘要 我们在本文中从一个完全不同的观点提出了一个用于求解无约束最优化问题 的拟合算法.算法中的迭代方向是从函数拟合中得到,而不是由传统的拟牛顿方程得到. 此方法有许多好的性质,并且在较弱的假设下证明算法是线性收敛的. In this paper, we proposes a modified fitting algorithm from a total different point of view for unconstrained optimization. In algorithm the iterative direction is from the function fitting other than the traditional quasi-Newton equation. Our method has many good properties and is linearly convergent under some mild assumptions.
作者 王薇 徐以凡
出处 《运筹学学报》 CSCD 北大核心 2003年第1期46-52,共7页 Operations Research Transactions
基金 Department of Mathematics,Shanghai University,Shanghai,200436 上海大学数学系,上海,200436.
关键词 无约束极值问题 拟合方法 正基 强凸函数 收敛性 迭代方向 Fitting, positive basis, strong convex function, convergence.
  • 引文网络
  • 相关文献

参考文献7

  • 1K. Schittkowski, More Test Examplesfor Nonlinear Programming Codes, Springer-Verlag,Berlin, 1987.
  • 2C. Davis, The Theorem of Positive Linear Independent, Amear, J. Math., 76 (1954)733-746.
  • 3F. Wu and X. Y. Guei, A Kind of Variable Metric Algorithm with n + 1 Parameters,ACTA Mathematica Sinica (in Chinese), 24, 1981, 6-16.
  • 4H. Y. Huang, Uniformly Approach to Quadratically Convergent Algorithm for FunctionMinimization, JOTA, 5, 1970,
  • 5W. C. Yu, Positive Basis and a Class of Direct Search Technique. Scientia Sinica,Mathematics(Ⅰ) (in Chinese), 1979, 53-68.
  • 6R. T. Rockafellar, Convex Analysis, Prentice Hall, 1970.
  • 7S. Q. Wu, The Decreasing Algorithm with Non-accurate Line Search and Its ConvergentProperties, ACTA Mathematica Sinica (in Chineso), 31:2, 1988, 228-240.

同被引文献13

引证文献1

二级引证文献3

;
使用帮助 返回顶部