A Switching Criterion in Hybrid Quasi-Newton BFGS - Steepest Descent Direction

Two modified methods for unconstrained optimization are presented. The methods employ a hybrid descent direction strategy which uses a linear convex combination of quasi-Newton BFGS and steepest descent as search direction. A switching criterion is derived based on the First and Second order Kuhn-T...

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Main Authors: Abu Hassan, Malik, Monsi, Mansor, Leong, Wah June
Format: Article
Language:English
English
Published: Universiti Putra Malaysia Press 1999
Online Access:http://psasir.upm.edu.my/id/eprint/3467/1/A_Switching_Criterion_in_Hybrid_Quasi-Newton.pdf
http://psasir.upm.edu.my/id/eprint/3467/
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Institution: Universiti Putra Malaysia
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spelling my.upm.eprints.34672013-05-27T07:08:45Z http://psasir.upm.edu.my/id/eprint/3467/ A Switching Criterion in Hybrid Quasi-Newton BFGS - Steepest Descent Direction Abu Hassan, Malik Monsi, Mansor Leong, Wah June Two modified methods for unconstrained optimization are presented. The methods employ a hybrid descent direction strategy which uses a linear convex combination of quasi-Newton BFGS and steepest descent as search direction. A switching criterion is derived based on the First and Second order Kuhn-Tucker condition. The switching criterion can be viewed as a way to change between quasi-Newton and steepest descent step by matching the Kuhn-Tucker condition. This is to ensure that no potential feasible moves away from the current descent step to the other one that reduced the value of the objective function. Numerical results are also presented, which suggest that an improvement has been achieved compared with the BFGS algorithm. Universiti Putra Malaysia Press 1999 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/3467/1/A_Switching_Criterion_in_Hybrid_Quasi-Newton.pdf Abu Hassan, Malik and Monsi, Mansor and Leong, Wah June (1999) A Switching Criterion in Hybrid Quasi-Newton BFGS - Steepest Descent Direction. Pertanika Journal of Science & Technology, 7 (2). pp. 111-123. ISSN 0128-7680 English
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
English
description Two modified methods for unconstrained optimization are presented. The methods employ a hybrid descent direction strategy which uses a linear convex combination of quasi-Newton BFGS and steepest descent as search direction. A switching criterion is derived based on the First and Second order Kuhn-Tucker condition. The switching criterion can be viewed as a way to change between quasi-Newton and steepest descent step by matching the Kuhn-Tucker condition. This is to ensure that no potential feasible moves away from the current descent step to the other one that reduced the value of the objective function. Numerical results are also presented, which suggest that an improvement has been achieved compared with the BFGS algorithm.
format Article
author Abu Hassan, Malik
Monsi, Mansor
Leong, Wah June
spellingShingle Abu Hassan, Malik
Monsi, Mansor
Leong, Wah June
A Switching Criterion in Hybrid Quasi-Newton BFGS - Steepest Descent Direction
author_facet Abu Hassan, Malik
Monsi, Mansor
Leong, Wah June
author_sort Abu Hassan, Malik
title A Switching Criterion in Hybrid Quasi-Newton BFGS - Steepest Descent Direction
title_short A Switching Criterion in Hybrid Quasi-Newton BFGS - Steepest Descent Direction
title_full A Switching Criterion in Hybrid Quasi-Newton BFGS - Steepest Descent Direction
title_fullStr A Switching Criterion in Hybrid Quasi-Newton BFGS - Steepest Descent Direction
title_full_unstemmed A Switching Criterion in Hybrid Quasi-Newton BFGS - Steepest Descent Direction
title_sort switching criterion in hybrid quasi-newton bfgs - steepest descent direction
publisher Universiti Putra Malaysia Press
publishDate 1999
url http://psasir.upm.edu.my/id/eprint/3467/1/A_Switching_Criterion_in_Hybrid_Quasi-Newton.pdf
http://psasir.upm.edu.my/id/eprint/3467/
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