Hybrid BFGS-ZMRI methods with global convergence properties

In this paper, we focus on the steepest descent and quasi-Newton method in solving unconstrained optimization problem. Therefore, we develop a new search direction for hybrid BFGS-ZMRI method with global convergence properties. Based on the numerical result, our method shows significant improvement...

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Bibliographic Details
Main Authors: Abidin, Zubai’ah Zainal, ‘Aini, Nurul, Husin, Siti Farhana, Rivaie, Mohd, Mamat, Mustafa
Format: Conference Proceeding
Language:English
Subjects:
Convergence
Iterative methods
Nonlinear programming
Quasi Newton methods
Online Access:Get full text
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Summary:In this paper, we focus on the steepest descent and quasi-Newton method in solving unconstrained optimization problem. Therefore, we develop a new search direction for hybrid BFGS-ZMRI method with global convergence properties. Based on the numerical result, our method shows significant improvement in the number of iteration and CPU time.
ISSN:0094-243X
1551-7616
DOI:10.1063/1.5041570