We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
MULTIPLE USE OF BACKTRACKING LINE SEARCH IN UNCONSTRAINED OPTIMIZATION.
- Authors
Ivanov, Branislav; Shaini, Bilall I.; Stanimirović, Predrag S.
- Abstract
The class of gradient methods 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 respect to well-known traditional methods.
- Subjects
CONJUGATE gradient methods; MOTIVATION (Psychology); PERFORMANCES
- Publication
Facta Universitatis, Series: Mathematics & Informatics, 2020, Vol 35, Issue 5, p1417
- ISSN
0352-9665
- Publication type
Article
- DOI
10.22190/FUMI2005417I