Numerical experiments on the conjugate gradient method with and without line search

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dc.contributor.authorAjimoti, Adams
dc.contributor.authorBamigbola, Olabode Matthias
dc.date.accessioned2019-04-23T08:50:41Z
dc.date.available2019-04-23T08:50:41Z
dc.date.issued2016
dc.descriptionPublication outlet: International Journal of Applied Science and Mathematical Theory 2(1), 1- 18en_US
dc.description.abstractThe conjugate gradient method CGM is an effective iterative method which is widely used for solving large-scale unconstrained optimization problems due to its low memory requirement. The efficiency of the CGM depends majorly on the step-size. Line search technique has been used in various literatures to obtain the step-size. A very recent development is to obtain the step-size with a unified formula which is refereed to as step-size without line search. Hence, in this work, we present numerical experiments for well-known CGMs such as Fletcher-Reeves, Bamigbola-Ali-Nwaeze, Polak-Ribiere, Dai-Yuan, Liu-Storey, Hesten-Stiefel, Conjugate-Descent, Hager-Zhang and Gradient Search Conjugacy methods. Numerical results obtained are graphically illustrated using performance profiling software to compare numerical efficiency of five inexact line searches namely Armijo, Goldstein, Weak, Strong and Approximate Wolfe and two formulae for estimating the step-size without line search which are Wu formula and Ajimoti-Bamigbola formula.en_US
dc.identifier.citationAjimoti and Bamigbola (2016)en_US
dc.identifier.urihttp://hdl.handle.net/123456789/1779
dc.language.isoenen_US
dc.publisherInternational Institute of Academic Research and Developmenten_US
dc.subjectConjugate gradient method,en_US
dc.subjectUnconstrained optimizationen_US
dc.subjectStep-size without line searchen_US
dc.titleNumerical experiments on the conjugate gradient method with and without line searchen_US
dc.typeArticleen_US

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