A new full Nesterov-Todd step feasible interior-point method for convex quadratic symmetric cone optimization
dc.contributor.author | Wang, G. | |
dc.contributor.author | Yu, C. | |
dc.contributor.author | Teo, Kok Lay | |
dc.date.accessioned | 2017-01-30T13:41:23Z | |
dc.date.available | 2017-01-30T13:41:23Z | |
dc.date.created | 2013-11-11T20:00:32Z | |
dc.date.issued | 2013 | |
dc.identifier.citation | Wang, G.Q. and Yu, C.J. and Teo, K.L. 2013. A new full Nesterov-Todd step feasible interior-point method for convex quadratic symmetric cone optimization. Applied Mathematics and Computations. 221: pp. 329-343. | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/34134 | |
dc.identifier.doi | 10.1016/j.amc.2013.06.064 | |
dc.description.abstract |
In this paper, we generalize the classical primal–dual logarithmic barrier method for linear optimization to convex quadratic optimization over symmetric cone by using Euclidean Jordan algebras. The symmetrization of the search directions used in this paper is based on the Nesterov–Todd scaling scheme, and only full Nesterov–Todd step is used at each iteration. We derive the iteration bound that matches the currently best known iteration bound for small-update methods, namely, O(√rlog4/ε. Some preliminary numerical results are provided to demonstrate the computational performance of the proposed algorithm. | |
dc.publisher | Elsevier Inc. | |
dc.subject | polynomial complexity | |
dc.subject | convex quadratic optimization | |
dc.subject | interior-point methods | |
dc.subject | Euclidean Jordan algebras | |
dc.subject | small-update method | |
dc.title | A new full Nesterov-Todd step feasible interior-point method for convex quadratic symmetric cone optimization | |
dc.type | Journal Article | |
dcterms.source.volume | 221 | |
dcterms.source.startPage | 329 | |
dcterms.source.endPage | 343 | |
dcterms.source.issn | 0096-3003 | |
dcterms.source.title | Applied Mathematics and Computations | |
curtin.department | ||
curtin.accessStatus | Fulltext not available |