A human centred hybrid MAS and meta-heuristics based system for simultaneously supporting scheduling and plant layout adjustment

Detalhes bibliográficos
Autor(a) principal: Alves, Filipe
Data de Publicação: 2018
Outros Autores: Varela, Maria Leonilde R., Rocha, Ana Maria A.C., Pereira, Ana I., Leitão, Paulo
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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spelling 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)
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instacron:RCAAP
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collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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