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Digital Library of the
European Council for Modelling and Simulation |
Title: |
Investigation On Optimization Of Process Parameters And Chemical
Reactor Geometry By Evolutionary Algorithms |
Authors: |
Tran Trong Dao, Ivan Zelinka |
Published in: |
(2009).ECMS
2009 Proceedings edited by J. Otamendi, A. Bargiela, J. L. Montes, L. M. Doncel
Pedrera. European Council for Modeling and
Simulation. doi:10.7148/2009 ISBN: 978-0-9553018-8-9 23rd
European Conference on Modelling and Simulation, Madrid, June
9-12, 2009 |
Citation
format: |
Dao, T. T., & Zelinka, I. (2009). Investigation On Optimization Of
Process Parameters And Chemical Reactor Geometry By Evolutionary Algorithms.
ECMS 2009 Proceedings edited by J. Otamendi, A. Bargiela, J. L. Montes, L. M. Doncel Pedrera (pp.
84-92). European Council for Modeling and Simulation. doi:10.7148/2009-0084-0092 |
DOI: |
http://dx.doi.org/10.7148/2009-0084-0092 |
Abstract: |
The present work aims to employ
evolutionary algorithms (EAs) to optimize an
industrial chemical process. A unique combination of the simplified
fundamental theory and direct hands-on computer simulation is used to present
the modeling of a dynamic chemical engineering process in a highly understandable way. The main aim
is to use them for analysis of dynamical system behaviour,
especially of a given chemical reactor. A non-linear mathematical model is
required to describe the dynamic behaviour of batch
process; this justifies the use of evolutionary method of the EAs to deal with this process. Two algorithms -
differential evolution and self-organizing migrating algorithm are used in
this investigation. Differential Evolution is an evolutionary optimization technique which is exceptionally simple, significantly
faster & robust at numerical optimization and is more likely to find a
function’s true global optimum. SOMA is also robust algorithm in sense of
global extreme searching. In this way, in order to optimize the process, the EAs code is coupled with the rigorous model of the
reactor. Both algorithms (SOMA, DE) have been applied 100 times in order to
find the optimum of process parameters and the reactor geometry. The results
show that the EAs are used successfully in the
process optimization. |
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