Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 김선영 | * |
dc.date.accessioned | 2016-08-28T11:08:51Z | - |
dc.date.available | 2016-08-28T11:08:51Z | - |
dc.date.issued | 2001 | * |
dc.identifier.issn | 1055-6788 | * |
dc.identifier.other | OAK-900 | * |
dc.identifier.uri | https://dspace.ewha.ac.kr/handle/2015.oak/218905 | - |
dc.description.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. | * |
dc.language | English | * |
dc.title | Second order cone programming relaxation of nonconvex quadratic optimization problems | * |
dc.type | Article | * |
dc.relation.issue | 3-4 | * |
dc.relation.volume | 15 | * |
dc.relation.index | SCIE | * |
dc.relation.index | SCOPUS | * |
dc.relation.startpage | 201 | * |
dc.relation.lastpage | 224 | * |
dc.relation.journaltitle | Optimization Methods and Software | * |
dc.identifier.wosid | WOS:000172546200002 | * |
dc.identifier.scopusid | 2-s2.0-0036455609 | * |
dc.author.google | Kim S. | * |
dc.author.google | Kojima M. | * |
dc.contributor.scopusid | 김선영(57221275622) | * |
dc.date.modifydate | 20231116113048 | * |