A Spectral Conjugate Gradient Method for Unconstrained Optimization |
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| Authors: | E G Birgin J M Martínez |
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| Institution: | Department of Computer Science, IME-USP, University of S?o Paulo, Rua do Mat?o, 1010 - Cidade Universitária, 05508-900 S?o Paulo SP, Brazil egbirgin@ime.usp.br, BR
Department of Applied Mathematics, IMECC-UNICAMP, University of Campinas, CP 6065, 13081-970 Campinas SP, Brazil martinez@ime.unicamp.br, BR
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| Abstract: | A family of scaled conjugate gradient algorithms for large-scale unconstrained minimization is defined. The Perry, the Polak—Ribière
and the Fletcher—Reeves formulae are compared using a spectral scaling derived from Raydan's spectral gradient optimization
method. The best combination of formula, scaling and initial choice of step-length is compared against well known algorithms
using a classical set of problems. An additional comparison involving an ill-conditioned estimation problem in Optics is presented.
Accepted 22 August 2000. Online publication 26 February 2001. |
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| Keywords: | , Unconstrained minimization, Spectral gradient method, Conjugate gradients, AMS Classification, 49M07, 49M10, 90C06,,,,,,65K, |
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