An evolutionary multi-objective optimization system for earthworks

Detalhes bibliográficos
Autor(a) principal: Parente, Manuel
Data de Publicação: 2015
Outros Autores: Cortez, Paulo, Correia, A. Gomes
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/1822/38251
Resumo: Earthworks involve the levelling or shaping of a target area through the moving or processing of the ground surface. Most construction projects require earthworks, which are heavily dependent on mechanical equipment (e.g., excavators, trucks and compactors). Often, earthworks are the most costly and time-consuming component of infrastructure constructions (e.g., road, railway and airports) and current pressure for higher productivity and safety highlights the need to optimize earthworks, which is a nontrivial task. Most previous attempts at tackling this problem focus on single-objective optimization of partial processes or aspects of earthworks, overlooking the advantages of a multi-objective and global optimization. This work describes a novel optimization system based on an evolutionary multi-objective approach, capable of globally optimizing several objectives simultaneously and dynamically. The proposed system views an earthwork construction as a production line, where the goal is to optimize resources under two crucial criteria (costs and duration) and focus the evolutionary search (non-dominated sorting genetic algorithm-II) on compaction allocation, using linear programming to distribute the remaining equipment (e.g., excavators). Several experiments were held using real-world data from a Portuguese construction site, showing that the proposed system is quite competitive when compared with current manual earthwork equipment allocation.
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spelling An evolutionary multi-objective optimization system for earthworksEarthworksEvolutionary computationMulti-objective optimizationArtificial intelligenceEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e InformáticaEngenharia e Tecnologia::Engenharia CivilScience & TechnologyEarthworks involve the levelling or shaping of a target area through the moving or processing of the ground surface. Most construction projects require earthworks, which are heavily dependent on mechanical equipment (e.g., excavators, trucks and compactors). Often, earthworks are the most costly and time-consuming component of infrastructure constructions (e.g., road, railway and airports) and current pressure for higher productivity and safety highlights the need to optimize earthworks, which is a nontrivial task. Most previous attempts at tackling this problem focus on single-objective optimization of partial processes or aspects of earthworks, overlooking the advantages of a multi-objective and global optimization. This work describes a novel optimization system based on an evolutionary multi-objective approach, capable of globally optimizing several objectives simultaneously and dynamically. The proposed system views an earthwork construction as a production line, where the goal is to optimize resources under two crucial criteria (costs and duration) and focus the evolutionary search (non-dominated sorting genetic algorithm-II) on compaction allocation, using linear programming to distribute the remaining equipment (e.g., excavators). Several experiments were held using real-world data from a Portuguese construction site, showing that the proposed system is quite competitive when compared with current manual earthwork equipment allocation.The authors wish to thank FCT for the financial support under the doctoral Grant SFRH/BD/71501/2010, as well as the construction company that kindly provided the real-world data. Also, we wish to thank Olaf Mersmann for kindly providing the R code for the SMS-EMOA algorithm.ElsevierUniversidade do MinhoParente, ManuelCortez, PauloCorreia, A. Gomes2015-112015-11-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/38251engParente, M., Cortez, P., & Correia, A. G. (2015). An evolutionary multi-objective optimization system for earthworks. Expert Systems with Applications, 42(19), 6674-6685. doi: 10.1016/j.eswa.2015.04.0510957-417410.1016/j.eswa.2015.04.051The original publication is available at: http://authors.elsevier.com/sd/article/S0957417415002936info: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:RCAAP2023-07-21T12:27:25Zoai:repositorium.sdum.uminho.pt:1822/38251Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:21:59.711142Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv An evolutionary multi-objective optimization system for earthworks
title An evolutionary multi-objective optimization system for earthworks
spellingShingle An evolutionary multi-objective optimization system for earthworks
Parente, Manuel
Earthworks
Evolutionary computation
Multi-objective optimization
Artificial intelligence
Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
Engenharia e Tecnologia::Engenharia Civil
Science & Technology
title_short An evolutionary multi-objective optimization system for earthworks
title_full An evolutionary multi-objective optimization system for earthworks
title_fullStr An evolutionary multi-objective optimization system for earthworks
title_full_unstemmed An evolutionary multi-objective optimization system for earthworks
title_sort An evolutionary multi-objective optimization system for earthworks
author Parente, Manuel
author_facet Parente, Manuel
Cortez, Paulo
Correia, A. Gomes
author_role author
author2 Cortez, Paulo
Correia, A. Gomes
author2_role author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Parente, Manuel
Cortez, Paulo
Correia, A. Gomes
dc.subject.por.fl_str_mv Earthworks
Evolutionary computation
Multi-objective optimization
Artificial intelligence
Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
Engenharia e Tecnologia::Engenharia Civil
Science & Technology
topic Earthworks
Evolutionary computation
Multi-objective optimization
Artificial intelligence
Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
Engenharia e Tecnologia::Engenharia Civil
Science & Technology
description Earthworks involve the levelling or shaping of a target area through the moving or processing of the ground surface. Most construction projects require earthworks, which are heavily dependent on mechanical equipment (e.g., excavators, trucks and compactors). Often, earthworks are the most costly and time-consuming component of infrastructure constructions (e.g., road, railway and airports) and current pressure for higher productivity and safety highlights the need to optimize earthworks, which is a nontrivial task. Most previous attempts at tackling this problem focus on single-objective optimization of partial processes or aspects of earthworks, overlooking the advantages of a multi-objective and global optimization. This work describes a novel optimization system based on an evolutionary multi-objective approach, capable of globally optimizing several objectives simultaneously and dynamically. The proposed system views an earthwork construction as a production line, where the goal is to optimize resources under two crucial criteria (costs and duration) and focus the evolutionary search (non-dominated sorting genetic algorithm-II) on compaction allocation, using linear programming to distribute the remaining equipment (e.g., excavators). Several experiments were held using real-world data from a Portuguese construction site, showing that the proposed system is quite competitive when compared with current manual earthwork equipment allocation.
publishDate 2015
dc.date.none.fl_str_mv 2015-11
2015-11-01T00:00:00Z
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/1822/38251
url http://hdl.handle.net/1822/38251
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Parente, M., Cortez, P., & Correia, A. G. (2015). An evolutionary multi-objective optimization system for earthworks. Expert Systems with Applications, 42(19), 6674-6685. doi: 10.1016/j.eswa.2015.04.051
0957-4174
10.1016/j.eswa.2015.04.051
The original publication is available at: http://authors.elsevier.com/sd/article/S0957417415002936
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 Elsevier
publisher.none.fl_str_mv Elsevier
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
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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 Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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