A global hybrid derivative-free method for high-dimensional systems of nonlinear equations-Reference-Cited by-同舟云学术

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A global hybrid derivative-free method for high-dimensional systems of nonlinear equations

Published:2019-11-04 Issue:1 Volume:75 Page:93-112
ISSN:0926-6003
Container-title:Computational Optimization and Applications
language:en
Short-container-title:Comput Optim Appl

Author:

Begiato Rodolfo G.^ORCID,Custódio Ana L.,Gomes-Ruggiero Márcia A.

Funder

Fundação para a Ciência e a Tecnologia

Fundação de Amparo à Pesquisa do Estado de São Paulo

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computational Mathematics,Control and Optimization

Link

http://link.springer.com/content/pdf/10.1007/s10589-019-00149-y.pdf

Reference15 articles.

1. Armijo, L.: Minimization of functions having Lipschitz continuous first partial derivatives. Pac. J. Math. 16, 1–3 (1966)

2. Barzilai, J., Borwein, J.M.: Two-point step size gradient methods. IMA J. Numer. Anal. 8, 141–148 (1988)

3. Chamberlain, R.M., Powell, M.J.D., Lemarechal, C., Pedersen, H.C.: The watchdog technique for forcing convergence in algorithms for constrained optimization. In: Buckley, A.G., Goffin, J.L. (eds.) Algorithms for Constrained Minimization of Smooth Nonlinear Functions. Mathematical Programming Studies, vol. 16, pp. 1–17. Springer, Berlin (1982)

4. Dembo, R.S., Eisenstat, S.C., Steihaug, T.: Inexact Newton methods. SIAM J. Numer. Anal. 19, 400–408 (1982)

5. Dolan, E.D., Moré, J.J.: Benchmarking optimization software with performance profiles. Math. Program. 91, 201–213 (2002)

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1. A Hybrid Computational Intelligence Method of Newton's Method and Genetic Algorithm for Solving Compatible Nonlinear Equations;Applied Mathematics and Nonlinear Sciences;2022-07-15

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