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dc.contributor.authorDang, Y.Z.
dc.contributor.authorSun, Jie
dc.contributor.authorZhang, Su
dc.date.accessioned2023-03-09T08:00:33Z
dc.date.available2023-03-09T08:00:33Z
dc.date.issued2019
dc.identifier.citationDang, Y.Z. and Sun, J. and Zhang, S. 2019. Double projection algorithms for solving the split feasibility problems. Journal of Industrial and Management Optimization. 15 (4): pp. 2023-2034.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/90788
dc.identifier.doi10.3934/jimo.2018135
dc.description.abstract

We propose two new double projection algorithms for solving the split feasibility problem (SFP). Different from the extragradient projection algorithms, the proposed algorithms do not require fixed stepsize and do not employ the same projection region at different projection steps. We adopt flexible rules for selecting the stepsize and the projection region. The proposed algorithms are shown to be convergent under certain assumptions. Numerical experiments show that the proposed methods appear to be more efficient than the relaxed- CQ algorithm.

dc.languageEnglish
dc.publisherAMER INST MATHEMATICAL SCIENCES-AIMS
dc.relation.sponsoredbyhttp://purl.org/au-research/grants/arc/DP160102819
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectScience & Technology
dc.subjectTechnology
dc.subjectPhysical Sciences
dc.subjectEngineering, Multidisciplinary
dc.subjectOperations Research & Management Science
dc.subjectMathematics, Interdisciplinary Applications
dc.subjectEngineering
dc.subjectMathematics
dc.subjectArmijo-type line search
dc.subjectconvergence analysis
dc.subjectdouble projection algorithm
dc.subjectoptimization
dc.subjectsplit feasibility problem
dc.subjectEXTRAGRADIENT METHOD
dc.subjectCQ ALGORITHM
dc.subjectSETS
dc.titleDouble projection algorithms for solving the split feasibility problems
dc.typeJournal Article
dcterms.source.volume15
dcterms.source.number4
dcterms.source.startPage2023
dcterms.source.endPage2034
dcterms.source.issn1547-5816
dcterms.source.titleJournal of Industrial and Management Optimization
dc.date.updated2023-03-09T08:00:32Z
curtin.departmentSchool of Elec Eng, Comp and Math Sci (EECMS)
curtin.accessStatusOpen access
curtin.facultyFaculty of Science and Engineering
curtin.contributor.orcidSun, Jie [0000-0001-5611-1672]
curtin.contributor.researcheridSun, Jie [B-7926-2016] [G-3522-2010]
dcterms.source.eissn1553-166X
curtin.contributor.scopusauthoridSun, Jie [16312754600] [57190212842]


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