1. Parameter estimation of a pulp digester model with derivative-free optimization strategies
- Author
-
Florbela P. Fernandes, João C. Seiça, Natércia C. P. Fernandes, Andrey Romanenko, and Lino O. Santos
- Subjects
Mathematical optimization ,Optimization problem ,Estimation theory ,Pulp (paper) ,engineering.material ,Pulp dgester model ,Nonlinear system ,Bounded function ,Derivative-free optimization ,Simulated annealing ,engineering ,Derivativo free optimization ,Global optimization ,Mathematics - Abstract
The work concerns the parameter estimation in the context of the mechanistic modelling of a pulp digester. The problem is cast as a box bounded nonlinear global optimization problem in order to minimize the mismatch between the model outputs with the experimental data observed at a real pulp and paper plant. MCSFilter and Simulated Annealing global optimization methods were used to solve the optimization problem. While the former took longer to converge to the global minimum, the latter terminated faster at a significantly higher value of the objective function and, thus, failed to find the global solution.The work concerns the parameter estimation in the context of the mechanistic modelling of a pulp digester. The problem is cast as a box bounded nonlinear global optimization problem in order to minimize the mismatch between the model outputs with the experimental data observed at a real pulp and paper plant. MCSFilter and Simulated Annealing global optimization methods were used to solve the optimization problem. While the former took longer to converge to the global minimum, the latter terminated faster at a significantly higher value of the objective function and, thus, failed to find the global solution.
- Published
- 2017