A new representation in evolutionary algorithms for the optimization of bioprocesses

Bibliographic Details
Main Author: Rocha, Miguel
Publication Date: 2005
Other Authors: Rocha, I., Ferreira, Eugénio C.
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: https://hdl.handle.net/1822/3015
Summary: Evolutionary Algorithms (EAs) have been used to achieve optimal feedforward control in a number of fed-batch fermentation processes. Typically, the optimization purpose is to set the optimal feeding trajectory, being the feeding profile over time given by a piecewise linear function, in order to reduce the number of parameters to the optimization algorithm. In this work, a novel representation scheme for the encoding of the feeding trajectory over time is proposed. Each gene in the variable sized chromosome has two components: a time label and the real value of the variable. The new approach is compared with a traditional real-valued EA, with chromosomes of constant size and fixed discretization steps. Three distinct case studies are presented, taken from previous work from the authors and literature, all considering the optimization of fed-batch fermentation processes. The experimental results show that the proposed approach is capable of results better or at the same level of quality of the best traditional EAs and is able to automatically evolve the best discretization steps for each case, thus simplifying the EA's setup.
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spelling A new representation in evolutionary algorithms for the optimization of bioprocessesFed-batch fermentation optimizationOptimization of feeding trajectoriesReal-valued representationsVariable size chromosomesScience & TechnologyEvolutionary Algorithms (EAs) have been used to achieve optimal feedforward control in a number of fed-batch fermentation processes. Typically, the optimization purpose is to set the optimal feeding trajectory, being the feeding profile over time given by a piecewise linear function, in order to reduce the number of parameters to the optimization algorithm. In this work, a novel representation scheme for the encoding of the feeding trajectory over time is proposed. Each gene in the variable sized chromosome has two components: a time label and the real value of the variable. The new approach is compared with a traditional real-valued EA, with chromosomes of constant size and fixed discretization steps. Three distinct case studies are presented, taken from previous work from the authors and literature, all considering the optimization of fed-batch fermentation processes. The experimental results show that the proposed approach is capable of results better or at the same level of quality of the best traditional EAs and is able to automatically evolve the best discretization steps for each case, thus simplifying the EA's setup.Fundação para a Ciência e Tecnologia (FCT) - 59899/EIA/POSC/2004.IEEEUniversidade do MinhoRocha, MiguelRocha, I.Ferreira, Eugénio C.2005-092005-09-01T00:00:00Zconference paperinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://hdl.handle.net/1822/3015engIEEE CONFERENCE ON EVOLUTIONARY COMPUTATION, Edimburgo, 2005 - "IEEE Conference on Evolutionary Computation : proceedings". Edimburgo : IEEE Press, 2005. ISBN 0-7803-9363-5. p. 484-490.0-7803-9363-5info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-11T07:20:30Zoai:repositorium.sdum.uminho.pt:1822/3015Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T16:23:40.921743Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv A new representation in evolutionary algorithms for the optimization of bioprocesses
title A new representation in evolutionary algorithms for the optimization of bioprocesses
spellingShingle A new representation in evolutionary algorithms for the optimization of bioprocesses
Rocha, Miguel
Fed-batch fermentation optimization
Optimization of feeding trajectories
Real-valued representations
Variable size chromosomes
Science & Technology
title_short A new representation in evolutionary algorithms for the optimization of bioprocesses
title_full A new representation in evolutionary algorithms for the optimization of bioprocesses
title_fullStr A new representation in evolutionary algorithms for the optimization of bioprocesses
title_full_unstemmed A new representation in evolutionary algorithms for the optimization of bioprocesses
title_sort A new representation in evolutionary algorithms for the optimization of bioprocesses
author Rocha, Miguel
author_facet Rocha, Miguel
Rocha, I.
Ferreira, Eugénio C.
author_role author
author2 Rocha, I.
Ferreira, Eugénio C.
author2_role author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Rocha, Miguel
Rocha, I.
Ferreira, Eugénio C.
dc.subject.por.fl_str_mv Fed-batch fermentation optimization
Optimization of feeding trajectories
Real-valued representations
Variable size chromosomes
Science & Technology
topic Fed-batch fermentation optimization
Optimization of feeding trajectories
Real-valued representations
Variable size chromosomes
Science & Technology
description Evolutionary Algorithms (EAs) have been used to achieve optimal feedforward control in a number of fed-batch fermentation processes. Typically, the optimization purpose is to set the optimal feeding trajectory, being the feeding profile over time given by a piecewise linear function, in order to reduce the number of parameters to the optimization algorithm. In this work, a novel representation scheme for the encoding of the feeding trajectory over time is proposed. Each gene in the variable sized chromosome has two components: a time label and the real value of the variable. The new approach is compared with a traditional real-valued EA, with chromosomes of constant size and fixed discretization steps. Three distinct case studies are presented, taken from previous work from the authors and literature, all considering the optimization of fed-batch fermentation processes. The experimental results show that the proposed approach is capable of results better or at the same level of quality of the best traditional EAs and is able to automatically evolve the best discretization steps for each case, thus simplifying the EA's setup.
publishDate 2005
dc.date.none.fl_str_mv 2005-09
2005-09-01T00:00:00Z
dc.type.driver.fl_str_mv conference paper
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://hdl.handle.net/1822/3015
url https://hdl.handle.net/1822/3015
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv IEEE CONFERENCE ON EVOLUTIONARY COMPUTATION, Edimburgo, 2005 - "IEEE Conference on Evolutionary Computation : proceedings". Edimburgo : IEEE Press, 2005. ISBN 0-7803-9363-5. p. 484-490.
0-7803-9363-5
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv IEEE
publisher.none.fl_str_mv IEEE
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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