Prikaz osnovnih podataka o dokumentu

dc.contributor.authorPetrović, Milena
dc.contributor.authorRakočević, Vladimir
dc.contributor.authorValjarević, Dragana
dc.contributor.authorIlić, Dejan
dc.date.accessioned2023-04-24T10:59:59Z
dc.date.available2023-04-24T10:59:59Z
dc.date.issued2019-12-03
dc.identifier.citationProjekat br.174025, Ministarstvo prosvete, nauke i tehnološkog razvoja Republike Srbijeen_US
dc.identifier.citationProjekat br.174024, Ministarstvo prosvete, nauke i tehnološkog razvoja Republike Srbijeen_US
dc.identifier.urihttps://platon.pr.ac.rs/handle/123456789/1259
dc.description.abstractWe introduce a hybrid gradient model for solving unconstrained optimization problems based on one specific accelerated gradient iteration. Having applied a three term hybridization relation on transformed accelerated double step size model, we develop an efficient hybrid accelerated scheme. We determine an iterative step size variable using Backtracking line search technique in which we take an optimally calculated starting value for the posed method. In convergence analysis, we show that the proposed method is at least linearly convergent on the sets of uniformly convex functions and strictly convex quadratic functions. Numerical computations confirm a significant improvement compared with some relevant hybrid and accelerated gradient processes. More precisely, subject to the number of iterations, the CPU time metric and the number of evaluations of the objective function, defined process outperforms comparative schemes multiple times.en_US
dc.language.isoen_USen_US
dc.publisherSpringeren_US
dc.titleA note on hybridization process applied on transformed double step size modelen_US
dc.title.alternativeNumerical Algorithmsen_US
dc.typeclanak-u-casopisuen_US
dc.description.versionpublishedVersionen_US
dc.identifier.doihttps://doi.org/10.1007/s11075-019-00821-8
dc.citation.volume85
dc.citation.spage449
dc.citation.epage465
dc.subject.keywordsUnconstrained optimizationen_US
dc.subject.keywordsLine searchen_US
dc.subject.keywordsGradient descent methodsen_US
dc.subject.keywordsNewton methoden_US
dc.subject.keywordsConvergence rateen_US
dc.type.mCategoryM21aen_US
dc.type.mCategoryclosedAccessen_US
dc.type.mCategoryM21aen_US
dc.type.mCategoryclosedAccessen_US


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