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New Inexact Line Search Method for Unconstrained Optimization

dc.contributor.authorShi, Zhen-Junen_US
dc.contributor.authorShen, Jieen_US
dc.date.accessioned2006-09-11T15:46:52Z
dc.date.available2006-09-11T15:46:52Z
dc.date.issued2005-11en_US
dc.identifier.citationShi, Z. J.; Shen, J.; (2005). "New Inexact Line Search Method for Unconstrained Optimization." Journal of Optimization Theory and Applications 127(2): 425-446. <http://hdl.handle.net/2027.42/45195>en_US
dc.identifier.issn0022-3239en_US
dc.identifier.issn1573-2878en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/45195
dc.description.abstractWe propose a new inexact line search rule and analyze the global convergence and convergence rate of related descent methods. The new line search rule is similar to the Armijo line-search rule and contains it as a special case. We can choose a larger stepsize in each line-search procedure and maintain the global convergence of related line-search methods. This idea can make us design new line-search methods in some wider sense. In some special cases, the new descent method can reduce to the Barzilai and Borewein method. Numerical results show that the new line-search methods are efficient for solving unconstrained optimization problems.en_US
dc.format.extent149659 bytes
dc.format.extent3115 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherKluwer Academic Publishers-Plenum Publishers; Springer Science+Business Media, Inc.en_US
dc.subject.otherUnconstrained Optimizationen_US
dc.subject.otherCalculus of Variations and Optimal Controlen_US
dc.subject.otherApplications of Mathematicsen_US
dc.subject.otherMathematicsen_US
dc.subject.otherTheory of Computationen_US
dc.subject.otherOptimizationen_US
dc.subject.otherOptimizationen_US
dc.subject.otherEngineering, Generalen_US
dc.subject.otherOperations Research/Decision Theoryen_US
dc.subject.otherInexact Line Searchen_US
dc.subject.otherGlobal Convergenceen_US
dc.subject.otherConvergence Rateen_US
dc.titleNew Inexact Line Search Method for Unconstrained Optimizationen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelMathematicsen_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Computer and Information Science, University of Michigan, Dearborn, Michiganen_US
dc.contributor.affiliationotherCollege of Operations Research and Management, Qufu Normal University, Rizhao, Shandong, PRC; Institute of Computational Mathematics and Scientific/Engineering Computing, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Rizhao, Beijing, Shandong, PRCen_US
dc.contributor.affiliationumcampusDearbornen_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/45195/1/10957_2005_Article_6553.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1007/s10957-005-6553-6en_US
dc.identifier.sourceJournal of Optimization Theory and Applicationsen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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