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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

A structured diagonal Hessian approximation method with evaluation complexity analysis for nonlinear least squares

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Autor(es):
Mohammad, Hassan [1] ; Santos, Sandra A. [2]
Número total de Autores: 2
Afiliação do(s) autor(es):
[1] Bayero Univ, Fac Phys Sci, Dept Math Sci, Kano - Nigeria
[2] Univ Estadual Campinas, Dept Appl Math, Inst Math Stat & Sci Comp, Campinas, SP - Brazil
Número total de Afiliações: 2
Tipo de documento: Artigo Científico
Fonte: COMPUTATIONAL & APPLIED MATHEMATICS; v. 37, n. 5, p. 6619-6653, NOV 2018.
Citações Web of Science: 1
Resumo

This work proposes a Jacobian-free strategy for addressing large-scale nonlinear least-squares problems, in which structured secant conditions are used to define a diagonal approximation for the Hessian matrix. Proper safeguards are devised to ensure descent directions along the generated sequence. Worst-case evaluation analysis is provided within the framework of a non-monotone line search. Numerical experiments contextualize the proposed strategy, by addressing structured problems from the literature, also solved by related and recently presented conjugate gradient and multivariate spectral gradient strategies, as well as the classic Fletcher-Reeves conjugate gradient, and the Raydan-Barzilai-Borwein methods. The comparative computational results show a favorable performance of the proposed approach, mainly as far as robustness is concerned. (AU)

Processo FAPESP: 13/05475-7 - Métodos computacionais de otimização
Beneficiário:Sandra Augusta Santos
Linha de fomento: Auxílio à Pesquisa - Temático
Processo FAPESP: 13/07375-0 - CeMEAI - Centro de Ciências Matemáticas Aplicadas à Indústria
Beneficiário:José Alberto Cuminato
Linha de fomento: Auxílio à Pesquisa - Centros de Pesquisa, Inovação e Difusão - CEPIDs