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1860799636870004736
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| building |
INTELEK Repository
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| collection |
Online Access
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| collectionurl |
https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072
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| date |
2016-12-28 15:45:15
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| eventvenue |
Kuala Lumpur, Malaysia
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| format |
Restricted Document
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| id |
6790
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| institution |
UniSZA
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| originalfilename |
1062-01-FH03-FIK-16-07679.jpg
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| person |
norman
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| recordtype |
oai_dc
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| resourceurl |
https://intelek.unisza.edu.my/intelek/pages/view.php?ref=6790
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| spelling |
6790 https://intelek.unisza.edu.my/intelek/pages/view.php?ref=6790 https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072 Restricted Document Conference Conference Paper image/jpeg inches 96 96 norman 775 1438 2016-12-28 15:45:15 1438x775 23 23 1062-01-FH03-FIK-16-07679.jpg UniSZA Private Access 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 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. 2nd International Conference on Mathematical Sciences and Statistics: Innovations Through Mathematical and Statistical Research Kuala Lumpur, Malaysia
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| spellingShingle |
A modified conjugate gradient coefficient with inexact line search for unconstrained optimization
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| summary |
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.
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| title |
A modified conjugate gradient coefficient with inexact line search for unconstrained optimization
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| title_full |
A modified conjugate gradient coefficient with inexact line search for unconstrained optimization
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| 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
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| title_short |
A modified conjugate gradient coefficient with inexact line search for unconstrained optimization
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| title_sort |
modified conjugate gradient coefficient with inexact line search for unconstrained optimization
|