A modified conjugate gradient coefficient with inexact line search for unconstrained optimization
Conjugate gradient (CG) method is a line search algorithm mostly known for its wide application in solving unconstrained optimization problems. Its low memory requirements and global convergence properties makes it one of the most preferred method in real life application such as in engineering and...
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my-unisza-ir.10622020-11-09T02:54:46Z http://eprints.unisza.edu.my/1062/ A modified conjugate gradient coefficient with inexact line search for unconstrained optimization Mustafa, M. Aini, N. Rivaie, M QA Mathematics QA75 Electronic computers. Computer science Conjugate gradient (CG) method is a line search algorithm mostly known for its wide application in solving unconstrained optimization problems. Its low memory requirements and global convergence properties makes it one of the most preferred method in real life application such as in engineering and business. In this paper, we present a new CG method based on AMR∗ and CD method for solving unconstrained optimization functions. The resulting algorithm is proven to have both the sufficient descent and global convergence properties under inexact line search. Numerical tests are conducted to assess the effectiveness of the new method in comparison to some previous CG methods. The results obtained indicate that our method is indeed superior. 2016 Conference or Workshop Item NonPeerReviewed image en http://eprints.unisza.edu.my/1062/1/FH03-FIK-16-07679.jpg Mustafa, M. and Aini, N. and Rivaie, M (2016) A modified conjugate gradient coefficient with inexact line search for unconstrained optimization. In: 2nd International Conference on Mathematical Sciences and Statistics: Innovations Through Mathematical and Statistical Research, 26-28 Jan 2016, Kuala Lumpur, Malaysia. |
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QA Mathematics QA75 Electronic computers. Computer science Mustafa, M. Aini, N. Rivaie, M A modified conjugate gradient coefficient with inexact line search for unconstrained optimization |
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Conjugate gradient (CG) method is a line search algorithm mostly known for its wide application in solving unconstrained optimization problems. Its low memory requirements and global convergence properties makes it one of the most preferred method in real life application such as in engineering and business. In this paper, we present a new CG method based on AMR∗ and CD method for solving unconstrained optimization functions. The resulting algorithm is proven to have both the sufficient descent and global convergence properties under inexact line search. Numerical tests are conducted to assess the effectiveness of the new method in comparison to some previous CG methods. The results obtained indicate that our method is indeed superior. |
format |
Conference or Workshop Item |
author |
Mustafa, M. Aini, N. Rivaie, M |
author_facet |
Mustafa, M. Aini, N. Rivaie, M |
author_sort |
Mustafa, M. |
title |
A modified conjugate gradient coefficient with inexact line search for unconstrained optimization |
title_short |
A modified conjugate gradient coefficient with inexact line search for unconstrained optimization |
title_full |
A modified conjugate gradient coefficient with inexact line search for unconstrained optimization |
title_fullStr |
A modified conjugate gradient coefficient with inexact line search for unconstrained optimization |
title_full_unstemmed |
A modified conjugate gradient coefficient with inexact line search for unconstrained optimization |
title_sort |
modified conjugate gradient coefficient with inexact line search for unconstrained optimization |
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2016 |
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http://eprints.unisza.edu.my/1062/1/FH03-FIK-16-07679.jpg http://eprints.unisza.edu.my/1062/ |
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