An Adaptive Nonmonotone Trust Region Method Based on a Structured Quasi Newton Equation for the Nonlinear Least Squares Problem

Autores/as

  • Graciela Croceri Universidad Nacional de Comahue, Argentina
  • Gonzalo Pizarro Universidad Nacional de Comahue, Argentina
  • Graciela Sottosanto Universidad Nacional del Comahue, Argentina

Palabras clave:

Trust region, Least Squares Problem, Structured Secant Approximation

Resumen

In this work an iterative method to solve the nonlinear least squares problem is presented. The algorithm combines a secant method with a strategy of nonmonotone trust region. In order to dene the quadratic model, the Hessian matrix is chosen using a secant approach that takes advantage of the structure of the problem, and the radius of the trust region is updated following an adaptive technique. Moreover, convergence properties of this algorithm are proved. The numerical experimentation, in which several ways of choosing the Hessian matrix are compared, shows the effiency and robustness of the method.

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Publicado

2017-09-19

Cómo citar

Croceri, G., Pizarro, G., & Sottosanto, G. (2017). An Adaptive Nonmonotone Trust Region Method Based on a Structured Quasi Newton Equation for the Nonlinear Least Squares Problem. SADIO Electronic Journal of Informatics and Operations Research, 16, 80-94. https://revistas.unlp.edu.ar/ejs/article/view/17584