DSpace at EWHA: Algorithm 883: SparsePOP - A sparse semidefinite programming relaxation of polynomial optimization problems

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DC Field	Value	Language
dc.contributor.author	김선영	*
dc.date.accessioned	2016-12-06T02:12:23Z	-
dc.date.available	2016-12-06T02:12:23Z	-
dc.date.issued	2008	*
dc.identifier.issn	0098-3500	*
dc.identifier.other	OAK-5076	*
dc.identifier.uri	https://dspace.ewha.ac.kr/handle/2015.oak/232990	-
dc.description.abstract	SparsePOP is a Matlab implementation of the sparse semidefinite programming (SDP) relaxation method for approximating a global optimal solution of a polynomial optimization problem (POP) proposed by Waki et al. [2006]. The sparse SDP relaxation exploits a sparse structure of polynomials in POPs when applying "a hierarchy of LMI relaxations of increasing dimensions" Lasserre [2006]. The efficiency of SparsePOP to approximate optimal solutions of POPs is thus increased, and larger-scale POPs can be handled. © 2008 ACM.	*
dc.language	English	*
dc.title	Algorithm 883: SparsePOP - A sparse semidefinite programming relaxation of polynomial optimization problems	*
dc.type	Article	*
dc.relation.issue	2	*
dc.relation.volume	35	*
dc.relation.index	SCI	*
dc.relation.index	SCIE	*
dc.relation.index	SCOPUS	*
dc.relation.journaltitle	ACM Transactions on Mathematical Software	*
dc.identifier.doi	10.1145/1377612.1377619	*
dc.identifier.wosid	WOS:000259433200007	*
dc.identifier.scopusid	2-s2.0-48849097802	*
dc.author.google	Waki H.	*
dc.author.google	Kim S.	*
dc.author.google	Kojima M.	*
dc.author.google	Muramatsu M.	*
dc.author.google	Sugimoto H.	*
dc.contributor.scopusid	김선영(57221275622)	*
dc.date.modifydate	20231116113048	*