A new representation in evolutionary algorithms for the optimization of bioprocesses
| Main Author: | |
|---|---|
| Publication Date: | 2005 |
| Other Authors: | , |
| 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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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 |
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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 |
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openAccess |
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application/pdf |
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IEEE |
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IEEE |
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