1. The CG-BFGS Method for Unconstrained Optimization Problems.
- Author
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Bin Ibrahim, Mohd Asrul Hery, Mamat, Mustafa, Leong Wah June, and Mohammad Sofi, Azfi Zaidi
- Subjects
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CONSTRAINED optimization , *QUASI-Newton methods , *ALGORITHMS , *APPROXIMATION theory , *NUMERICAL analysis , *STOCHASTIC convergence - Abstract
In this paper we present a new search direction known as the CG-BFGS method, which uses the search direction of the conjugate gradient method approach in the quasi-Newton methods. The new algorithm is compared with the quasi-Newton methods in terms of the number of iterations and CPU-time. The Broyden-Fletcher-Goldfarb-Shanno (BFGS) method is used as an updating formula for the approximation of the Hessian for both methods. Our numerical analysis provides strong evidence that our CG-BFGS method is more efficient than the ordinary BFGS method. Besides, we also prove that the new algorithm is globally convergent. [ABSTRACT FROM AUTHOR]
- Published
- 2014
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