| _version_ |
1860796852974125056
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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 |
2021-07-14 00:32:59
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| eventvenue |
Virtual, Online
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| format |
Restricted Document
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| id |
10431
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| institution |
UniSZA
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| originalfilename |
4406-01-FH03-FIK-21-54262.pdf
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| person |
Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML
like Gecko) Chrome/90.0.4430.212 Safari/537.36
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| recordtype |
oai_dc
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| resourceurl |
https://intelek.unisza.edu.my/intelek/pages/view.php?ref=10431
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| spelling |
10431 https://intelek.unisza.edu.my/intelek/pages/view.php?ref=10431 https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072 Restricted Document Conference Conference Paper application/pdf 5 1.6 Adobe Acrobat Pro DC 20 Paper Capture Plug-in Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML like Gecko) Chrome/90.0.4430.212 Safari/537.36 2021-07-14 00:32:59 4406-01-FH03-FIK-21-54262.pdf UniSZA Private Access New hybrid BFGS-CG method for solving unconstrained optimization Conjugate gradient method and quasi-Newton (QN) method are both well known solvers for solving unconstrained optimization problems. In this paper, we proposed a new conjugate gradient method denoted as Wan, Asrul and Mustafa (WAM) method. This WAM method is then combined with the QN method to produce a new hybrid search direction which is QN-WAM. Based on numerical results, the proposed hybrid method proved to be more efficient compared to the original quasi-Newton method and other hybrid methods. 1st International Recent Trends in Engineering, Advanced Computing and Technology Conference Virtual, Online
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| spellingShingle |
New hybrid BFGS-CG method for solving unconstrained optimization
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| summary |
Conjugate gradient method and quasi-Newton (QN) method are both well known solvers for solving unconstrained optimization problems. In this paper, we proposed a new conjugate gradient method denoted as Wan, Asrul and Mustafa (WAM) method. This WAM method is then combined with the QN method to produce a new hybrid search direction which is QN-WAM. Based on numerical results, the proposed hybrid method proved to be more efficient compared to the original quasi-Newton method and other hybrid methods.
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| title |
New hybrid BFGS-CG method for solving unconstrained optimization
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| title_full |
New hybrid BFGS-CG method for solving unconstrained optimization
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| title_fullStr |
New hybrid BFGS-CG method for solving unconstrained optimization
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| title_full_unstemmed |
New hybrid BFGS-CG method for solving unconstrained optimization
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| title_short |
New hybrid BFGS-CG method for solving unconstrained optimization
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| title_sort |
new hybrid bfgs-cg method for solving unconstrained optimization
|