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Second order cone programming relaxation of nonconvex quadratic optimization problems

Title
Second order cone programming relaxation of nonconvex quadratic optimization problems
Authors
Kim S.Kojima M.
Ewha Authors
김선영
SCOPUS Author ID
김선영scopus
Issue Date
2001
Journal Title
Optimization Methods and Software
ISSN
1055-6788JCR Link
Citation
vol. 15, no. 3-4, pp. 201 - 224
Indexed
SCIE; SCOPUS WOS scopus
Abstract
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. © 2001 OPA (Overseas Publishers Association) N.V. Published by license under the Gordon and Breach Science Publishers imprint, a member of the Taylor & Francis Group.
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자연과학대학 > 수학전공 > Journal papers
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