A descent derivative-free algorithm for nonlinear monotone equations with convex constraints
In this paper, we present a derivative-free algorithm for nonlinear monotone equations with convex constraints. The search direction is a product of a positive parameter and the negation of a residual vector. At each iteration step, the algorithm generates a descent direction independent from the li...
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Published in | R.A.I.R.O. Recherche opérationnelle Vol. 54; no. 2; pp. 489 - 505 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Paris
EDP Sciences
01.03.2020
|
Subjects | |
Online Access | Get full text |
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Summary: | In this paper, we present a derivative-free algorithm for nonlinear monotone equations with convex constraints. The search direction is a product of a positive parameter and the negation of a residual vector. At each iteration step, the algorithm generates a descent direction independent from the line search used. Under appropriate assumptions, the global convergence of the algorithm is given. Numerical experiments show the algorithm has advantages over the recently proposed algorithms by Gao and He (
Calcolo
55
(2018) 53) and Liu and Li (
Comput. Math. App.
70
(2015) 2442–2453). |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
ISSN: | 0399-0559 1290-3868 |
DOI: | 10.1051/ro/2020008 |