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All Journal International Journal of Business, Economics, and Social Development International Journal of Quantitative Research and Modeling
Yasir Salih
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Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Languange, Linguistic, Communication & Media Physics Social Sciences

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Journal : International Journal of Quantitative Research and Modeling

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A COMPARATIVE STUDY OF SOME MODIFICATIONS OF CG METHODS UNDER EXACT LINE SEARCH Yasir Salih; Mustafa Mamat; Sukono Sukono
International Journal of Quantitative Research and Modeling Vol 1, No 1 (2020)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (428.404 KB) | DOI: 10.46336/ijqrm.v1i1.2

Abstract

Conjugate Gradient (CG) method is a technique used in solving nonlinear unconstrained optimization problems. In this paper, we analysed the performance of two modifications and compared the results with the classical conjugate gradient methods of. These proposed methods possesse global convergence properties for general functions using exact line search. Numerical experiments show that the two modifications are more efficient for the test problems compared to classical CG coefficients.
Co-Authors Alit Kartiwa Komar Komar Mustafa Mamat Riaman Riaman Sukono Sukono