M. Fernández de Dios, Á. M. González Rueda, J. R. Banga, J. González Díaz, D. R. Penas
In this work, we address parameter estimation in models described by nonlinear ordinary differential equations (ODEs) using a direct transcription approach. Controls and state profiles are discretized, leading to a nonlinear programming (NLP) problem solvable via mathematical programming techniques. The main goal of this work is to analyze the potential of mathematical modeling and state-of-the-art solvers to handle these problems. For this purpose, an extensive numerical study on eight challenging parameter estimation problems in nonlinear dynamic biological systems is carried out. Different modeling aspects, such as discretization schemes and formulation variants, are explored. The use of global and local solvers provides insights into local optimality and identifiability challenges. Our approach yields promising results, surpassing previously reported capabilities in the literature.
Palabras clave: Parameter estimation, Dynamic modelling, Optimization, Mathematical programming
Programado
Métodos y aplicaciones de la IO II
13 de junio de 2025 09:00
Sala de prensa (MR 13)