A trust-region-approach for solving a parameter estimation problem from the biotechnology area

Authors:
Juan Ignacio Ardenghi;María Cristina Maciel;Adriana Beatriz Verdiell
Affiliations:
Department of Mathematics, Southern National University, Avenida Alem 1253, 8000 Bahía Blanca, Argentina;Department of Mathematics, Southern National University, Avenida Alem 1253, 8000 Bahía Blanca, Argentina;Department of Mathematics, Southern National University, Avenida Alem 1253, 8000 Bahía Blanca, Argentina
Venue:
Applied Numerical Mathematics - Special issue on applied and computational mathematics: Selected papers of the fourth PanAmerican workshop
Year:
2003

Citing 5
Cited 0

On the global convergence of trust region algorithms using inexact gradient information

SIAM Journal on Numerical Analysis
An Adaptive Nonlinear Least-Squares Algorithm

ACM Transactions on Mathematical Software (TOMS)
Trust-region methods

Trust-region methods
Computer Methods for Mathematical Computations

Computer Methods for Mathematical Computations
Numerical Methods for Unconstrained Optimization and Nonlinear Equations (Classics in Applied Mathematics, 16)

Numerical Methods for Unconstrained Optimization and Nonlinear Equations (Classics in Applied Mathematics, 16)

Quantified Score

Hi-index	0.00

Visualization

Abstract

Growth kinetics of microorganisms processes involves a parameter estimation problem, which is usually solved by using simulation techniques. A different approach is presented. It is based on a trust-region algorithm for nonlinear least squares problems with bound constraints. The global convergence properties of the algorithm are analyzed in the theory proposed by Verdiell.An important aspect of the algorithm is that first and second order information of the objective function can be approximated what is advantageous for the class of pointwise known functions. This feature makes the algorithm suitable to solve real-world problems. Encouraging preliminary results are presented.