Parameter estimation in nonlinear algebraic models via global optimization

The estimation of parameters in semi-empirical nonlinear models through the error-in-variables method has been widely studied from a computational standpoint. This method involves the minimization of a quadratic objective function subject to the model equations being satisfied. Due to the nonlinear...

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Vydáno v:Computers & chemical engineering Ročník 22; s. S213 - S220
Hlavní autoři: Esposito, William R., Floudas, Christodoulos A.
Médium: Journal Article Konferenční příspěvek
Jazyk:angličtina
Vydáno: Oxford Elsevier Ltd 01.01.1998
Elsevier
Témata:
Applications of mathematics to chemical engineering. Modeling. Simulation. Optimization
Applied sciences
Chemical engineering
Exact sciences and technology
Operational research and scientific management
Operational research. Management science
Optimization. Search problems
Non linear equation
Parameter estimation
Branch and bound method
Algebraic equation
Mathematical model
Modeling
Optimization
ISSN:0098-1354, 1873-4375
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Shrnutí:The estimation of parameters in semi-empirical nonlinear models through the error-in-variables method has been widely studied from a computational standpoint. This method involves the minimization of a quadratic objective function subject to the model equations being satisfied. Due to the nonlinear nature of these models, the resulting formulation is nonconvex in nature. The approaches to solve this problem presented so far in the literature, although computationally efficient, only offer convergence to a local solution of a model which may contain multiple minima. In this paper a global optimization approach based on a branch-and-bound framework will be presented to solve the error-in-variables formulation. Various estimation problems were solved and will be presented to illustrate the theoretical and computational aspects of the proposed method.
ISSN:0098-1354
1873-4375
DOI:10.1016/S0098-1354(98)00217-8