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dc.contributor.authorDang, Y.
dc.contributor.authorSun, Jie
dc.contributor.authorXu, Honglei
dc.date.accessioned2017-08-24T02:22:42Z
dc.date.available2017-08-24T02:22:42Z
dc.date.created2017-08-23T07:21:41Z
dc.date.issued2017
dc.identifier.citationDang, Y. and Sun, J. and Xu, H. 2017. Inertial accelerated algorithms for solving a split feasibility problem. Journal of Industrial and management optimization. 13 (3): pp. 1383-1394.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/56140
dc.identifier.doi10.3934/jimo.2016078
dc.description.abstract

Inspired by the inertial proximal algorithms for finding a zero of a maximal monotone operator, in this paper, we propose two inertial accel erated algorithms to solve the split feasibility problem. One is an inertial relaxed-CQ algorithm constructed by applying inertial technique to a relaxed- CQ algorithm, the other is a modified inertial relaxed-CQ algorithm which combines the KM method with the inertial relaxed-CQ algorithm. We prove their asymptotical convergence under some suitable conditions. Numerical re sults are reported to show the effectiveness of the proposed algorithms.

dc.publisherAmerican Institute of Mathematical Sciences
dc.relation.sponsoredbyhttp://purl.org/au-research/grants/arc/DP160102819
dc.titleInertial accelerated algorithms for solving a split feasibility problem
dc.typeJournal Article
dcterms.source.volume13
dcterms.source.number3
dcterms.source.startPage1383
dcterms.source.endPage1394
dcterms.source.issn1547-5816
dcterms.source.titleJournal of Industrial and Management Optimization
curtin.note

This is a pre-copy-editing, author-produced PDF of an article accepted for publication in Journal of Industrial and Management Optimization following peer review. The definitive publisher-authenticated version cited above is available online at: http://doi.org/10.3934/jimo.2016078

curtin.departmentDepartment of Mathematics and Statistics
curtin.accessStatusOpen access


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