Numerical Comparison of Line Search Criteria in Nonlinear Conjugate Gradient Algorithms


One of the open problems known to researchers on the application of nonlinear conjugate gradient methods for addressing unconstrained optimization problems is the influence of accuracy of linear search procedure on the performance of the conjugate gradient algorithm. Key to any CG algorithm is the computation of an optimalstep size for which many procedures have been postulated. In this paper, we assess and compare the performance of a modified Armijo and Wolfe line search procedures on three variants of nonlinear CGM by carrying out a numerical test. Experiments reveal that our modified procedure and the strong Wolfe procedures guaranteed fast convergence.

Keywords: Armijo line search, Nonlinear conjugate gradient method, Wolfe line search, large scale problems, unconstrained optimization problems

Unique Article ID: IJMSS-133
Article Review Status: Published

Pages: 14-24 (Download PDF)

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This work by European American Journals is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License

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