MULTIPLE USE OF BACKTRACKING LINE SEARCH IN UNCONSTRAINED OPTIMIZATION

Branislav Ivanov, Bilall I. Shaini, Predrag S. Stanimirović

DOI Number
https://doi.org/10.22190/FUMI2005417I
First page
1417
Last page
1438

Abstract


The gradient method is a very efficient iterative technique for solving unconstrained optimization problems. Motivated by recent modifications of some variants of the SM method, this study proposed two methods that are globally convergent as well as computationally efficient. Each of the methods is globally convergent under the influence of a backtracking line search. Results obtained from the numerical implementation of these methods and performance profiling show that the methods are very competitive with well-known traditional methods.


Keywords

unconstrained optimization; gradient methods; line search.

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References


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DOI: https://doi.org/10.22190/FUMI2005417I

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