Trust Region Newton With Conjugate Gradient Method

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dc.contributor.advisorGuta, Berhanu (PhD)
dc.contributor.authorLeul, Hewan
dc.date.accessioned2019-04-08T06:36:44Z
dc.date.accessioned2023-11-09T04:20:37Z
dc.date.available2019-04-08T06:36:44Z
dc.date.available2023-11-09T04:20:37Z
dc.date.issued2018-06-03
dc.description.abstractIn this project we give trust-region algorithms for nonlinear optimization. Trust-region methods are robust and can be applied to ill-conditioned problems. A conjugate gradient trust-region algorithm is presented to demonstrate the trust region approaches. Conver- gence properties of trust-region with conjugate gradient are given. A trust-region method subproblems for solving unconstrained optimization is proposed. At every iteration, we use the conjugate gradient method or its variation to solve the subproblems approximately. We show that this method has the same convergence properties as the trust-region method based on the conjugate gradient method. Numerical results show that this method is as reliable and more e cient in respect of iterations and evaluations using MATLAB.en_US
dc.identifier.urihttp://etd.aau.edu.et/handle/123456789/17644
dc.language.isoenen_US
dc.publisherAddis Ababa Universityen_US
dc.subjectLine Searchen_US
dc.subjectNewton Methoden_US
dc.subjectSteepest Descenten_US
dc.subjectConjugate Gradienten_US
dc.subjectTrust- Regionen_US
dc.titleTrust Region Newton With Conjugate Gradient Methoden_US
dc.typeThesisen_US

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