WSEAS Transactions on Mathematics
Print ISSN: 1109-2769, E-ISSN: 2224-2880
Volume 20, 2021
A Globally Convergent Hybrid FR-PRP Conjugate Gradient Method for Unconstrained Optimization Problems
Authors: , ,
Abstract: In this paper, a new conjugate gradient (CG) parameter is proposed through the convex combination of the Fletcher-Reeves (FR) and Polak-Ribiére-Polyak (PRP) CG update parameters such that the conjugacy condition of Dai-Liao is satisfied. The computational efficiency of the PRP method and the convergence profile of the FR method motivated the choice of these two CG methods. The corresponding CG algorithm satisfies the sufficient descent property and was shown to be globally convergent under the strong Wolfe line search procedure. Numerical tests on selected benchmark test functions show that the algorithm is efficient and very competitive in comparison with some existing classical methods.
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Keywords: Unconstrained optimization, convex combination, conjugate gradient method, conjugacy condition, hybridization
Pages: 736-744
DOI: 10.37394/23206.2021.20.78