Parallel Implementation of Successive Convex Relaxation Methods for Quadratic Optimization Problems

被引：0
作者：
Akiko Takeda
Katsuki Fujisawa
Yusuke Fukaya
Masakazu Kojima
机构：
[1] Toshiba Corporation,Department of Architecture
[2] Kyoto University,Department of Mathematical and Computing Sciences
[3] NS Solutions Corporation,undefined
[4] Tokyo Institute of Technology,undefined
来源：
Journal of Global Optimization | 2002年 / 24卷
关键词：
Nonconvex quadratic program; SDP relaxation; Lift-and-project LP relaxation; Lift-and-project procedure; Parallel computation; Global computing;
D O I：
暂无
中图分类号：
学科分类号：
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).
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页码：237 / 260
页数：23
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