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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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
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creator Abidin, Zubai’ah Zainal
‘Aini, Nurul
Husin, Siti Farhana
Rivaie, Mohd
Mamat, Mustafa
description 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.
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subjects Convergence
Iterative methods
Nonlinear programming
Quasi Newton methods
title Hybrid BFGS-ZMRI methods with global convergence properties
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