A Hybrid of Quasi-Newton Method with CG Method for Unconstrained Optimization
The quasi-Newton is a well-known method for solving small to medium-scale unconstrained optimization problems due to its simplicity and convergence. This leads to many modifications to improve its performance, and one of them is by hybridizing it with another optimization method. In this study , t...
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| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | en |
| Published: |
2019
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| Subjects: | |
| Online Access: | http://eprints.unisza.edu.my/1921/1/FH03-FIK-19-36121.pdf http://eprints.unisza.edu.my/1921/ |
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| Summary: | The quasi-Newton is a well-known method for solving small to medium-scale unconstrained optimization problems
due to its simplicity and convergence. This leads to many modifications to improve its performance, and one of them
is by hybridizing it with another optimization method. In this study , the quasi-Newton method is combined with the
ARM method, which is a type of conjugate gradient method. The resulting hybrid algorithm is globally convergent
under exact line search |
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