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Ibrahim, Mohd Asrul Hery; Mamat, Mustafa; Leong, Wah June

The hybrid BFGS-CG method in solving unconstrained optimization problems. (English) Zbl 1470.90159

Abstr. Appl. Anal. 2014, Article ID 507102, 6 p. (2014).
Summary: In solving large scale problems, the quasi-Newton method is known as the most efficient method in solving unconstrained optimization problems. Hence, a new hybrid method, known as the BFGS-CG method, has been created based on these properties, combining the search direction between conjugate gradient methods and quasi-Newton methods. In comparison to standard BFGS methods and conjugate gradient methods, the BFGS-CG method shows significant improvement in the total number of iterations and CPU time required to solve large scale unconstrained optimization problems. We also prove that the hybrid method is globally convergent.

Cited in 1 Document

MSC:

90C53 Methods of quasi-Newton type
90C30 Nonlinear programming

Software:

minpack; Genocop; SCALCG
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\textit{M. A. H. Ibrahim} et al., Abstr. Appl. Anal. 2014, Article ID 507102, 6 p. (2014; Zbl 1470.90159)
Full Text: DOI

References:

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