The CG-BFGS method for unconstrained optimization problems
| Format: | Restricted Document |
|---|
| _version_ | 1860799605102346240 |
|---|---|
| building | INTELEK Repository |
| collection | Online Access |
| collectionurl | https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072 |
| date | 2015-10-26 11:03:41 |
| eventvenue | Penang, Malaysia |
| format | Restricted Document |
| id | 6655 |
| institution | UniSZA |
| originalfilename | 0195-01-FH03-FIK-15-03960.jpg |
| person | UniSZA Unisza unisza |
| recordtype | oai_dc |
| resourceurl | https://intelek.unisza.edu.my/intelek/pages/view.php?ref=6655 |
| spelling | 6655 https://intelek.unisza.edu.my/intelek/pages/view.php?ref=6655 https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072 Restricted Document Conference Conference Paper UniSZA Unisza unisza image/jpeg inches 96 96 11 11 2015-10-26 11:03:41 790 1423x790 1423 0195-01-FH03-FIK-15-03960.jpg UniSZA Private Access The CG-BFGS method for unconstrained optimization problems In this paper we present a new search direction known as the CG-BFGS method, which uses the search direction of the conjugate gradient method approach in the quasi-Newton methods. The new algorithm is compared with the quasi-Newton methods in terms of the number of iterations and CPU-time. The Broyden-Fletcher-Goldfarb-Shanno (BFGS) method is used as an updating formula for the approximation of the Hessian for both methods. Our numerical analysis provides strong evidence that our CG-BFGS method is more efficient than the ordinary BFGS method. Besides, we also prove that the new algorithm is globally convergent 21st National Symposium on Mathematical Sciences: Germination of Mathematical Sciences Education and Research Towards Global Sustainability, SKSM 21 Penang, Malaysia |
| spellingShingle | The CG-BFGS method for unconstrained optimization problems |
| summary | In this paper we present a new search direction known as the CG-BFGS method, which uses the search direction of the conjugate gradient method approach in the quasi-Newton methods. The new algorithm is compared with the quasi-Newton methods in terms of the number of iterations and CPU-time. The Broyden-Fletcher-Goldfarb-Shanno (BFGS) method is used as an updating formula for the approximation of the Hessian for both methods. Our numerical analysis provides strong evidence that our CG-BFGS method is more efficient than the ordinary BFGS method. Besides, we also prove that the new algorithm is globally convergent |
| title | The CG-BFGS method for unconstrained optimization problems |
| title_full | The CG-BFGS method for unconstrained optimization problems |
| title_fullStr | The CG-BFGS method for unconstrained optimization problems |
| title_full_unstemmed | The CG-BFGS method for unconstrained optimization problems |
| title_short | The CG-BFGS method for unconstrained optimization problems |
| title_sort | cg-bfgs method for unconstrained optimization problems |