A human centred hybrid MAS and meta-heuristics based system for simultaneously supporting scheduling and plant layout adjustment
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10198/20114 |
Resumo: | Manufacturing activities and production control are constantly growing. Despite this, it is necessary to improve the increasing variety of scheduling and layout adjustments for dynamic and flexible responses in volatile environments with disruptions or failures. Faced with the lack of realistic and practical manufacturing scenarios, this approach allows simulating and solving the problem of job shop scheduling on a production system by taking advantage of genetic algorithm and particle swarm optimization algorithm combined with the flexibility and robustness of a multi-agent system and dynamic rescheduling alternatives. Therefore, this hybrid decision support system intends to obtain optimized solutions and enable humans to interact with the system to properly adjust priorities or refine setups or solutions, in an interactive and user-friendly way. The system allows to evaluate the optimization performance of each one of the algorithms proposed, as well as to obtain decentralization in responsiveness and dynamic decisions for rescheduling due to the occurance of unexpected events. |
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A human centred hybrid MAS and meta-heuristics based system for simultaneously supporting scheduling and plant layout adjustmentHuman-centredIndustry 4.0MetaheuristicsMulti-agent systemOptimizationSchedulingManufacturing activities and production control are constantly growing. Despite this, it is necessary to improve the increasing variety of scheduling and layout adjustments for dynamic and flexible responses in volatile environments with disruptions or failures. Faced with the lack of realistic and practical manufacturing scenarios, this approach allows simulating and solving the problem of job shop scheduling on a production system by taking advantage of genetic algorithm and particle swarm optimization algorithm combined with the flexibility and robustness of a multi-agent system and dynamic rescheduling alternatives. Therefore, this hybrid decision support system intends to obtain optimized solutions and enable humans to interact with the system to properly adjust priorities or refine setups or solutions, in an interactive and user-friendly way. The system allows to evaluate the optimization performance of each one of the algorithms proposed, as well as to obtain decentralization in responsiveness and dynamic decisions for rescheduling due to the occurance of unexpected events.This work has been supported by FCT - Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2019.Biblioteca Digital do IPBAlves, FilipeVarela, Maria Leonilde R.Rocha, Ana Maria A.C.Pereira, Ana I.Leitão, Paulo2018-01-19T10:00:00Z20192019-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10198/20114engAlves, Filipe; Varela, Maria Leonilde R.; Rocha, Ana Maria A.C.; Pereira, Ana I.; Leitão, Paulo (2019). A human centred hybrid MAS and meta-heuristics based system for simultaneously supporting scheduling and plant layout adjustment. FME Transactions. ISSN 1451-2092. 47, p. 699-7101451-209210.5937/fmet1904699Ainfo: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:RCAAP2023-11-21T10:45:57Zoai:bibliotecadigital.ipb.pt:10198/20114Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T23:10:54.313971Repositório 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 |
A human centred hybrid MAS and meta-heuristics based system for simultaneously supporting scheduling and plant layout adjustment |
title |
A human centred hybrid MAS and meta-heuristics based system for simultaneously supporting scheduling and plant layout adjustment |
spellingShingle |
A human centred hybrid MAS and meta-heuristics based system for simultaneously supporting scheduling and plant layout adjustment Alves, Filipe Human-centred Industry 4.0 Metaheuristics Multi-agent system Optimization Scheduling |
title_short |
A human centred hybrid MAS and meta-heuristics based system for simultaneously supporting scheduling and plant layout adjustment |
title_full |
A human centred hybrid MAS and meta-heuristics based system for simultaneously supporting scheduling and plant layout adjustment |
title_fullStr |
A human centred hybrid MAS and meta-heuristics based system for simultaneously supporting scheduling and plant layout adjustment |
title_full_unstemmed |
A human centred hybrid MAS and meta-heuristics based system for simultaneously supporting scheduling and plant layout adjustment |
title_sort |
A human centred hybrid MAS and meta-heuristics based system for simultaneously supporting scheduling and plant layout adjustment |
author |
Alves, Filipe |
author_facet |
Alves, Filipe Varela, Maria Leonilde R. Rocha, Ana Maria A.C. Pereira, Ana I. Leitão, Paulo |
author_role |
author |
author2 |
Varela, Maria Leonilde R. Rocha, Ana Maria A.C. Pereira, Ana I. Leitão, Paulo |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Biblioteca Digital do IPB |
dc.contributor.author.fl_str_mv |
Alves, Filipe Varela, Maria Leonilde R. Rocha, Ana Maria A.C. Pereira, Ana I. Leitão, Paulo |
dc.subject.por.fl_str_mv |
Human-centred Industry 4.0 Metaheuristics Multi-agent system Optimization Scheduling |
topic |
Human-centred Industry 4.0 Metaheuristics Multi-agent system Optimization Scheduling |
description |
Manufacturing activities and production control are constantly growing. Despite this, it is necessary to improve the increasing variety of scheduling and layout adjustments for dynamic and flexible responses in volatile environments with disruptions or failures. Faced with the lack of realistic and practical manufacturing scenarios, this approach allows simulating and solving the problem of job shop scheduling on a production system by taking advantage of genetic algorithm and particle swarm optimization algorithm combined with the flexibility and robustness of a multi-agent system and dynamic rescheduling alternatives. Therefore, this hybrid decision support system intends to obtain optimized solutions and enable humans to interact with the system to properly adjust priorities or refine setups or solutions, in an interactive and user-friendly way. The system allows to evaluate the optimization performance of each one of the algorithms proposed, as well as to obtain decentralization in responsiveness and dynamic decisions for rescheduling due to the occurance of unexpected events. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-01-19T10:00:00Z 2019 2019-01-01T00:00:00Z |
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/10198/20114 |
url |
http://hdl.handle.net/10198/20114 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Alves, Filipe; Varela, Maria Leonilde R.; Rocha, Ana Maria A.C.; Pereira, Ana I.; Leitão, Paulo (2019). A human centred hybrid MAS and meta-heuristics based system for simultaneously supporting scheduling and plant layout adjustment. FME Transactions. ISSN 1451-2092. 47, p. 699-710 1451-2092 10.5937/fmet1904699A |
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.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 |
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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 |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799135375542714368 |