View : 214 Download: 0

Sums of squares and semidefinite program relaxations for polynomial optimization problems with structured sparsity

Title
Sums of squares and semidefinite program relaxations for polynomial optimization problems with structured sparsity
Authors
Waki H.Kim S.Kojima M.Muramatsu M.
Ewha Authors
김선영
SCOPUS Author ID
김선영scopus
Issue Date
2007
Journal Title
SIAM Journal on Optimization
ISSN
1052-6234JCR Link
Citation
SIAM Journal on Optimization vol. 17, no. 1, pp. 218 - 242
Indexed
SCIE; SCOPUS WOS scopus
Document Type
Article
Abstract
Unconstrained and inequality constrained sparse polynomial optimization problems (POPs) are considered. A correlative sparsity pattern graph is defined to find a certain sparse structure in the objective and constraint polynomials of a POP. Based on this graph, sets of the supports for sums of squares (SOS) polynomials that lead to efficient SOS and semidefinite program (SDP) relaxations are obtained. Numerical results from various test problems are included to show the improved performance of the SOS and SDP relaxations. © 2006 Society for Industrial and Applied Mathematics.
Show the fulltext
DOI
10.1137/050623802
Appears in Collections:
자연과학대학 > 수학전공 > Journal papers
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML


qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE