A new modified RMIL CG method with global convergence properties
The Conjugate Gradient (CG) method is an approach commonly used to solve large-scale optimization issues. This method is considered efficient for its properties of global convergence and low requirements for memory. In this study, we proposed a novel CG coefficient γ using the method developed by...
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| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2019
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| Subjects: | |
| Online Access: | http://eprints.unisza.edu.my/1899/1/FH03-FIK-20-36378.pdf http://eprints.unisza.edu.my/1899/ |
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| Summary: | The Conjugate Gradient (CG) method is an approach commonly used to solve large-scale optimization issues. This
method is considered efficient for its properties of global convergence and low requirements for memory. In this
study, we proposed a novel CG coefficient γ using the method developed by Rivaie-Mustafa-Ismail-Leong (RMIL).
The suggested technique is shown to have global convergence under exact line search. This is reinforced by the
numerical test results, which concurrently indicate that the new CG method is more efficient in comparison with the
current CG methods. |
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