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Investigation on Optimization of Process Parameters and Chemical Reactor Geometry by Evolutionary Algorithms

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dc.title Investigation on Optimization of Process Parameters and Chemical Reactor Geometry by Evolutionary Algorithms en
dc.contributor.author Dao, Tran Trong
dc.contributor.author Zelinka, Ivan
dc.relation.ispartof 23rd European Conference on Modelling and Simulation (ECMS 2009)
dc.identifier.isbn 978-0-9553018-8-9
dc.date.issued 2009
dc.citation.spage 84
dc.citation.epage 92
dc.event.title 23rd European Conference on Modelling and Simulation (ECMS)
dc.event.location Madrid
utb.event.state-en Spain
utb.event.state-cs Španělsko
dc.event.sdate 2009-06-09
dc.event.edate 2009-06-12
dc.type conferenceObject
dc.language.iso en
dc.publisher European Council for Modelling and Simulation (ECMS) en
dc.relation.uri http://www.scs-europe.net/conf/ecms2009/ecms2009%20CD/ecms2009%20accepted%20papers/is_0096_d7e7485d.pdf
dc.subject Simulation en
dc.subject Optimization en
dc.subject Evolutionary algorithms en
dc.subject Differential evolution en
dc.subject Self-organizing migrating algorithm en
dc.description.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. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1002793
utb.identifier.rivid RIV/70883521:28140/09:63507984!RIV10-MSM-28140___
utb.identifier.obdid 43861087
utb.identifier.scopus 2-s2.0-84857765367
utb.identifier.wok 000302016000013
utb.source d-wok
dc.date.accessioned 2012-06-04T11:34:08Z
dc.date.available 2012-06-04T11:34:08Z
utb.contributor.internalauthor Dao, Tran Trong
utb.contributor.internalauthor Zelinka, Ivan
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