SUPERLINEAR PRIMAL-DUAL AFFINE SCALING ALGORITHMS FOR LCP

被引：13

作者：

MONTEIRO, RDC

WRIGHT, SJ

机构：

[1] ARGONNE NATL LAB,DIV MATH & COMP SCI,ARGONNE,IL 60439

[2] GEORGIA INST TECHNOL,SCH IND & SYST ENGN,ATLANTA,GA 30332

来源：

MATHEMATICAL PROGRAMMING | 1995年 / 69卷 / 02期

基金：

美国国家科学基金会;

关键词：

INTERIOR-POINT METHODS; PRIMAL-DUAL AFFINE SCALING; LINEAR PROGRAMMING; LINEAR COMPLEMENTARITY;

D O I：

10.1007/BF01585562

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

We describe an interior-point algorithm for monotone linear complementarity problems in which primal-dual affine scaling is used to generate the search directions. The algorithm is shown to have global and superlinear convergence with Q-order up to (but not including) two. The technique is shown to be consistent with a potential-reduction algorithm, yielding the first potential-reduction algorithm that is both globally and superlinearly convergent.

引用

页码：311 / 333

页数：23

共 23 条

[1]

JI J, 1991, TR9123 RIC U DEP MAT

[2]

JI J, 1991, PREDICTION CORRECTOR

[3] HOMOTOPY CONTINUATION METHODS FOR NONLINEAR COMPLEMENTARITY-PROBLEMS [J].