Parallel implementation of successive convex relaxation methods for quadratic optimization problems

被引：5

作者：

Takeda, A ^{[1
]}

Fujisawa, K

Fukaya, Y

Kojima, M

机构：

[1] Toshiba Co Ltd, Kawasaki, Kanagawa 210, Japan

[2] Kyoto Univ, Dept Architecture, Kyoto, Japan

[3] NS Solut Corp, Tokyo, Japan

[4] Tokyo Inst Technol, Dept Math & Comp Sci, Tokyo 152, Japan

来源：

JOURNAL OF GLOBAL OPTIMIZATION | 2002年 / 24卷 / 02期

关键词：

nonconvex quadratic program; SDP relaxation; lift-and-project LP relaxation; lift-and-project procedure; parallel computation; global computing;

D O I：

10.1023/A:1020299805773

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 ; 12 ; 1201 ; 1202 ; 120202 ;

摘要：

As computing resources continue to improve, global solutions for larger size quadrically constrained optimization problems become more achievable. In this paper, we focus on larger size problems and get accurate bounds for optimal values of such problems with the successive use of SDP relaxations on a parallel computing system called Ninf (Network-based Information Library for high performance computing).

引用

页码：237 / 260

页数：24

共 28 条

[1] A branch and cut algorithm for nonconvex quadratically constrained quadratic programming [J].