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Cluster Validation Analysis on Attribute Relative of Soft-Set Theory Read chapter Read first chapter

2017 | OriginalPaper | Chapter

A New Search Direction for Broyden’s Family Method in Solving Unconstrained Optimization Problems

Authors : Mohd Asrul Hery Ibrahim, Zailani Abdullah, Mohd Ashlyzan Razik, Tutut Herawan

Published in: Recent Advances on Soft Computing and Data Mining

Publisher: Springer International Publishing

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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.

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Metadata
Title
A New Search Direction for Broyden’s Family Method in Solving Unconstrained Optimization Problems
Authors
Mohd Asrul Hery Ibrahim
Zailani Abdullah
Mohd Ashlyzan Razik
Tutut Herawan
Copyright Year
2017
Book
Recent Advances on Soft Computing and Data Mining

Print ISBN: 978-3-319-51279-2

Electronic ISBN: 978-3-319-51281-5

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-51281-5_7

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