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

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

Research output: Contribution to journalArticle

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 languageEnglish
Pages (from-to)153-164
Number of pages12
JournalOptimization Methods and Software
Volume19
Issue number2
DOIs
Publication statusPublished - Apr 2004

Fingerprint

Unconstrained Optimization
BFGS Method
Quasi-Newton
Robust Methods
Nonlinear Optimization
Updating
Update
Optimization Problem
Numerical Results
Optimization problem
Nonlinear optimization

Keywords

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

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Software
  • Applied Mathematics
  • Control and Optimization
  • Management Science and Operations Research

Cite this

On the performance of switching BFGS/SR1 algorithms for unconstrained optimization. / Al-Baali, M.; Fuduli, A.; Musmanno, R.

In: Optimization Methods and Software, Vol. 19, No. 2, 04.2004, p. 153-164.

Research output: Contribution to journalArticle

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