Exploiting sparsity in primal-dual interior-point methods for semidefinite programming

被引：3

作者：

Katsuki Fujisawa

Masakazu Kojima

Kazuhide Nakata

机构：

[1] Tokyo Institute of Technology,Department of Mathematical and Computing Sciences

来源：

Mathematical Programming | 1997年 / 79卷

关键词：

Interior-point methods; Semidefinite programming; Sparsity;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

The Helmberg-Rendl-Vanderbei-Wolkowicz/Kojima-Shindoh-Hara/Monteiro and Nesterov-Todd search directions have been used in many primal-dual interior-point methods for semidefinite programs. This paper proposes an efficient method for computing the two directions when the semidefinite program to be solved is large scale and sparse.

引用

页码：235 / 253

页数：18

共 10 条

[1]

Helmberg C.(1996)An interior-point method for semidefinite programming SIAM Journal on Optimization 6 342-361

[2]

Rendl F.(1997)Interior-point methods for the monotone semidefinite linear complementarity problems SIAM Journal on Optimization 7 86-125

[3]

Vanderbei R.J.(1995)A recipe for semidefinite relaxation for (0,1) quadratic programming Journal of Global Optimization 7 51-73

[4]

Wolkowicz H.(undefined)undefined undefined undefined undefined-undefined

[5]

Kojima M.(undefined)undefined undefined undefined undefined-undefined

[6]

Shindoh S.(undefined)undefined undefined undefined undefined-undefined

[7]

Hara S.(undefined)undefined undefined undefined undefined-undefined

[8]

Poljak S.(undefined)undefined undefined undefined undefined-undefined

[9]

Rendl F.(undefined)undefined undefined undefined undefined-undefined

[10]

Wolkowicz H.(undefined)undefined undefined undefined undefined-undefined

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