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Erschienen in:
2017 | OriginalPaper | Buchkapitel
A New Search Direction for Broyden’s Family Method in Solving Unconstrained Optimization Problems
verfasst von : Mohd Asrul Hery Ibrahim, Zailani Abdullah, Mohd Ashlyzan Razik, Tutut Herawan
Erschienen in: Recent Advances on Soft Computing and Data Mining
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Abstract
The conjugate gradient method plays an important role in solving large scale problems and the quasi-Newton method is known as the most efficient method in solving unconstrained optimization problems. Hence, in this paper, we proposed a new hybrid method between conjugate gradient method and quasi-Newton method known as the CG-Broyden method. Then, the new hybrid method is compared with the quasi-Newton methods in terms of the number of iterations and CPU-time using Matlabin Windows 10 which has 4 GB RAM and running using an Intel ® Core ™ i5. Furthermore, the performance profile graphic is used to show the effectiveness of the new hybrid method.. Our numerical analysis provides strong evidence that our CG-Broyden method is more efficient than the ordinary Broyden method Besides, we also prove that the new algorithm is globally convergent.