Convergence rate of primal-dual reciprocal barrier Newton interior-point methods

被引:0
|
作者
El-Bakry, AS [1 ]
机构
[1] Univ Alexandria, Fac Sci, Dept Math, Alexandria, Egypt
来源
OPTIMIZATION METHODS & SOFTWARE | 1998年 / 9卷 / 1-3期
关键词
convergence rate; interior-point methods; reciprocal barrier function;
D O I
10.1080/10556789808805685
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Primal-dual interior-point methods for linear programming are often motivated by a certain nonlinear transformation of the Karush-Kuhn-Tucker conditions of the logarithmic barrier formulation. Recently, Nassar [5] studied the reciprocal barrier function formulation of the problem. Using a similar nonlinear transformation, he proved local convergence for Newton interior-point method on the resulting perturbed Karush-Kuhn-Tucker system. This result poses the question whether this method can exhibit fast convergence rate for linear programming. In this paper we prove that, for linear programming, Newton's method on the reciprocal barrier formulation exhibits at best Q-linear convergence rate. Moreover, an exact Q(1) factor is established which precludes fast linear convergence.
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页码:37 / 44
页数:8
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