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자연과학대학
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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
김선영
Issue Date
2001
Journal Title
Optimization Methods and Software
ISSN
1055-6788
Citation
Optimization Methods and Software vol. 15, no. 3-4, pp. 201 - 224
Indexed
SCIE; SCOPUS
Document Type
Article
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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