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dc.contributor.authorLi, J.
dc.contributor.authorWu, Z.
dc.contributor.authorWu, Changzhi
dc.contributor.authorLong, Q.
dc.contributor.authorWang, X.
dc.date.accessioned2017-01-30T13:54:44Z
dc.date.available2017-01-30T13:54:44Z
dc.date.created2015-10-29T04:09:04Z
dc.date.issued2015
dc.identifier.citationLi, J. and Wu, Z. and Wu, C. and Long, Q. and Wang, X. 2015. An Inexact Dual Fast Gradient-Projection Method for Separable Convex Optimization with Linear Coupled Constraints. Journal of Optimization Theory and Applications.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/36258
dc.identifier.doi10.1007/s10957-015-0757-1
dc.description.abstract

© 2015 Springer Science+Business Media New York In this paper, a class of separable convex optimization problems with linear coupled constraints is studied. According to the Lagrangian duality, the linear coupled constraints are appended to the objective function. Then, a fast gradient-projection method is introduced to update the Lagrangian multiplier, and an inexact solution method is proposed to solve the inner problems. The advantage of our proposed method is that the inner problems can be solved in an inexact and parallel manner. The established convergence results show that our proposed algorithm still achieves optimal convergence rate even though the inner problems are solved inexactly. Finally, several numerical experiments are presented to illustrate the efficiency and effectiveness of our proposed algorithm.

dc.publisherSpringer New York LLC
dc.relation.sponsoredbyhttp://purl.org/au-research/grants/arc/LP130100451
dc.titleAn Inexact Dual Fast Gradient-Projection Method for Separable Convex Optimization with Linear Coupled Constraints
dc.typeJournal Article
dcterms.source.issn0022-3239
dcterms.source.titleJournal of Optimization Theory and Applications
curtin.departmentDepartment of Construction Management
curtin.accessStatusFulltext not available


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