On the performance of switching BFGS/SR1 algorithms for unconstrained optimization

M. Al-Baali; A. Fuduli; R. Musmanno

doi:10.1080/10556780310001625019

On the performance of switching BFGS/SR1 algorithms for unconstrained optimization

M. Al-Baali, A. Fuduli, R. Musmanno^*

^*Corresponding author for this work

Mathematics & Statistics

Research output: Contribution to journal › Article › peer-review

3 Citations (Scopus)

Abstract

This paper studies some possible combinations of the best features of the quasi-Newton symmetric rank-one (SRI), BFGS and extra updating BFGS algorithms for solving nonlinear unconstrained optimization problems. These combinations depend on switching between the BFGS and SRI updates so that certain desirable properties are imposed. The presented numerical results show that the proposed switching algorithm outperforms the robust BFGS method.

Original language	English
Pages (from-to)	153-164
Number of pages	12
Journal	Optimization Methods and Software
Volume	19
Issue number	2
DOIs	https://doi.org/10.1080/10556780310001625019
Publication status	Published - Apr 2004

Keywords

BFGS and SRI updating methods
Switching and extra updating techniques
Unconstrained optimization

ASJC Scopus subject areas

Software
Control and Optimization
Applied Mathematics

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10.1080/10556780310001625019

Cite this

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abstract = "This paper studies some possible combinations of the best features of the quasi-Newton symmetric rank-one (SRI), BFGS and extra updating BFGS algorithms for solving nonlinear unconstrained optimization problems. These combinations depend on switching between the BFGS and SRI updates so that certain desirable properties are imposed. The presented numerical results show that the proposed switching algorithm outperforms the robust BFGS method.",

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AB - This paper studies some possible combinations of the best features of the quasi-Newton symmetric rank-one (SRI), BFGS and extra updating BFGS algorithms for solving nonlinear unconstrained optimization problems. These combinations depend on switching between the BFGS and SRI updates so that certain desirable properties are imposed. The presented numerical results show that the proposed switching algorithm outperforms the robust BFGS method.

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On the performance of switching BFGS/SR1 algorithms for unconstrained optimization

Abstract

Keywords

ASJC Scopus subject areas

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