Global optimization of energy and production in process industries: a genetic algorithm application

Detalhes bibliográficos
Autor(a) principal: Santos, Amâncio
Data de Publicação: 1999
Outros Autores: Dourado, António
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10316/4115
https://doi.org/10.1016/S0967-0661(98)00194-4
Resumo: The process industries exhibit an increasing need for efficient management of all the factors that can reduce their operating costs, leading to the necessity for a global multi-objective optimization methodology that will enable the generation of optimum strategies, fulfilling the required restrictions. In this paper, a genetic algorithm is developed and applied for the optimal assignment of all the production sections in a particular mill in the kraft pulp and paper industry, in order to optimize energy the costs and production rate changes. This system is intended to implement all programmed or forced maintenance shutdowns, as well as all the reductions imposed in production rates.
id RCAP_161f2b827ced51ac4faec4e1a2c2be00
oai_identifier_str oai:estudogeral.uc.pt:10316/4115
network_acronym_str RCAP
network_name_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository_id_str
spelling Global optimization of energy and production in process industries: a genetic algorithm applicationProduction controlScheduling algorithmsGenetic algorithmsGlobal optimizationPulp industryThe process industries exhibit an increasing need for efficient management of all the factors that can reduce their operating costs, leading to the necessity for a global multi-objective optimization methodology that will enable the generation of optimum strategies, fulfilling the required restrictions. In this paper, a genetic algorithm is developed and applied for the optimal assignment of all the production sections in a particular mill in the kraft pulp and paper industry, in order to optimize energy the costs and production rate changes. This system is intended to implement all programmed or forced maintenance shutdowns, as well as all the reductions imposed in production rates.http://www.sciencedirect.com/science/article/B6V2H-3WJFJY7-D/1/7465ac585e8d9ac2ef4ea20cafe987121999info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleaplication/PDFhttp://hdl.handle.net/10316/4115http://hdl.handle.net/10316/4115https://doi.org/10.1016/S0967-0661(98)00194-4engControl Engineering Practice. 7:4 (1999) 549-554Santos, AmâncioDourado, Antónioinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2020-11-06T16:59:56ZPortal AgregadorONG
dc.title.none.fl_str_mv Global optimization of energy and production in process industries: a genetic algorithm application
title Global optimization of energy and production in process industries: a genetic algorithm application
spellingShingle Global optimization of energy and production in process industries: a genetic algorithm application
Santos, Amâncio
Production control
Scheduling algorithms
Genetic algorithms
Global optimization
Pulp industry
title_short Global optimization of energy and production in process industries: a genetic algorithm application
title_full Global optimization of energy and production in process industries: a genetic algorithm application
title_fullStr Global optimization of energy and production in process industries: a genetic algorithm application
title_full_unstemmed Global optimization of energy and production in process industries: a genetic algorithm application
title_sort Global optimization of energy and production in process industries: a genetic algorithm application
author Santos, Amâncio
author_facet Santos, Amâncio
Dourado, António
author_role author
author2 Dourado, António
author2_role author
dc.contributor.author.fl_str_mv Santos, Amâncio
Dourado, António
dc.subject.por.fl_str_mv Production control
Scheduling algorithms
Genetic algorithms
Global optimization
Pulp industry
topic Production control
Scheduling algorithms
Genetic algorithms
Global optimization
Pulp industry
description The process industries exhibit an increasing need for efficient management of all the factors that can reduce their operating costs, leading to the necessity for a global multi-objective optimization methodology that will enable the generation of optimum strategies, fulfilling the required restrictions. In this paper, a genetic algorithm is developed and applied for the optimal assignment of all the production sections in a particular mill in the kraft pulp and paper industry, in order to optimize energy the costs and production rate changes. This system is intended to implement all programmed or forced maintenance shutdowns, as well as all the reductions imposed in production rates.
publishDate 1999
dc.date.none.fl_str_mv 1999
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10316/4115
http://hdl.handle.net/10316/4115
https://doi.org/10.1016/S0967-0661(98)00194-4
url http://hdl.handle.net/10316/4115
https://doi.org/10.1016/S0967-0661(98)00194-4
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Control Engineering Practice. 7:4 (1999) 549-554
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv aplication/PDF
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1777302670939258880