Second order cone programming relaxation of nonconvex quadratic optimization problems

被引：81

作者：

Kim, S

Kojima, M

机构：

[1] Ewha Womans Univ, Dept Math, Sudaemoon gu, Seoul 120750, South Korea

[2] Tokyo Inst Technol, Dept Math & Comp Sci, Meguro Ku, Tokyo 1528522, Japan

来源：

OPTIMIZATION METHODS & SOFTWARE | 2001年 / 15卷 / 3-4期

关键词：

second-order-cone program; lift-and-project convex relaxation method; nonconvex quadratic program; global optimization; primal-dual interior-point method;

D O I：

10.1080/10556780108805819

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

A disadvantage of the SDP (semidefinite programming) relaxation method for quadratic and/or combinatorial optimization problems lies in its expensive computational cost. This paper proposes a SOCP (second-order-cone programming) relaxation method, which strengthens the lift-and-project LP (linear programming) relaxation method by adding convex quadratic valid inequalities for the positive semidefinite cone involved in the SDP relaxation. Numerical experiments show that our SOCP relaxation is a reasonable compromise between the effectiveness of the SDP relaxation and the low computational cost of the lift-and-project LP relaxation.

引用

页码：201 / 224

页数：24

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