An Optimal Parameter for Dai–Liao Family of Conjugate Gradient Methods

M. Fatemi ()
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M. Fatemi: K. N. Toosi University of Technology

Journal of Optimization Theory and Applications, 2016, vol. 169, issue 2, No 12, 587-605

Abstract: Abstract We introduce a new efficient nonlinear conjugate gradient method for unconstrained optimization, based on minimizing a penalty function. Our penalty function combines the good properties of the linear conjugate gradient method using some penalty parameters. We show that the new method is a member of Dai–Liao family and, more importantly, propose an efficient Dai–Liao parameter by closely analyzing the penalty function. Numerical experiments show that the proposed parameter is promising.

Keywords: Conjugate gradient method; Dai–Liao family; Unconstrained optimization; Line search; 90C06; 90C26; 65Y20 (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10957-015-0786-9

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