CLC number: Q815; TP278
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 0000-00-00
Cited: 14
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ANDRÉS-TORO B., GIRÓN-SIERRA J.M., FERNÁNDEZ-BLANCO P., LÓPEZ-OROZCO J.A., BESADA-PORTAS E.. Multiobjective optimization and multivariable control of the beer fermentation process with the use of evolutionary algorithms[J]. Journal of Zhejiang University Science A, 2004, 5(4): 378-389.
@article{title="Multiobjective optimization and multivariable control of the beer fermentation process with the use of evolutionary algorithms",
author="ANDRÉS-TORO B., GIRÓN-SIERRA J.M., FERNÁNDEZ-BLANCO P., LÓPEZ-OROZCO J.A., BESADA-PORTAS E.",
journal="Journal of Zhejiang University Science A",
volume="5",
number="4",
pages="378-389",
year="2004",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2004.0378"
}
%0 Journal Article
%T Multiobjective optimization and multivariable control of the beer fermentation process with the use of evolutionary algorithms
%A ANDRÉ
%A S-TORO B.
%A GIRÓ
%A N-SIERRA J.M.
%A FERNÁ
%A NDEZ-BLANCO P.
%A LÓ
%A PEZ-OROZCO J.A.
%A BESADA-PORTAS E.
%J Journal of Zhejiang University SCIENCE A
%V 5
%N 4
%P 378-389
%@ 1869-1951
%D 2004
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.2004.0378
TY - JOUR
T1 - Multiobjective optimization and multivariable control of the beer fermentation process with the use of evolutionary algorithms
A1 - ANDRÉ
A1 - S-TORO B.
A1 - GIRÓ
A1 - N-SIERRA J.M.
A1 - FERNÁ
A1 - NDEZ-BLANCO P.
A1 - LÓ
A1 - PEZ-OROZCO J.A.
A1 - BESADA-PORTAS E.
J0 - Journal of Zhejiang University Science A
VL - 5
IS - 4
SP - 378
EP - 389
%@ 1869-1951
Y1 - 2004
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.2004.0378
Abstract: This paper describes empirical research on the model, optimization and supervisory control of beer fermentation. Conditions in the laboratory were made as similar as possible to brewery industry conditions. Since mathematical models that consider realistic industrial conditions were not available, a new mathematical model design involving industrial conditions was first developed. Batch fermentations are multiobjective dynamic processes that must be guided along optimal paths to obtain good results. The paper describes a direct way to apply a Pareto set approach with multiobjective evolutionary algorithms (MOEAs). Successful finding of optimal ways to drive these processes were reported. Once obtained, the mathematical fermentation model was used to optimize the fermentation process by using an intelligent control based on certain rules.
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