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dc.contributor.author김선영-
dc.date.accessioned2016-08-28T11:08:51Z-
dc.date.available2016-08-28T11:08:51Z-
dc.date.issued2001-
dc.identifier.issn1055-6788-
dc.identifier.otherOAK-900-
dc.identifier.urihttps://dspace.ewha.ac.kr/handle/2015.oak/218905-
dc.description.abstractA 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.-
dc.languageEnglish-
dc.titleSecond order cone programming relaxation of nonconvex quadratic optimization problems-
dc.typeArticle-
dc.relation.issue3-4-
dc.relation.volume15-
dc.relation.indexSCIE-
dc.relation.indexSCOPUS-
dc.relation.startpage201-
dc.relation.lastpage224-
dc.relation.journaltitleOptimization Methods and Software-
dc.identifier.wosidWOS:000172546200002-
dc.identifier.scopusid2-s2.0-0036455609-
dc.author.googleKim S.-
dc.author.googleKojima M.-
dc.contributor.scopusid김선영(57007276700)-
dc.date.modifydate20170601154045-
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자연과학대학 > 수학전공 > Journal papers
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