Artificial Bee Colony Algorithm Applied to Dynamic Flexible Job Shop Problems
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , , , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10174/28823 https://doi.org/FERREIRA, I., FIRME, B., MARTINS, M., COITO, T., VIEGAS, J., FIGUEIREDO, J., VIEIRA, S. SOUSA, J. [2020] Artificial Bee Colony Algorithm Applied to Dynamic Flexible Job Shop Problems. In: Lesot MJ. et al. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2020. Communications in Computer and Information Science, vol 1237. Springer, Cham. https://doi.org/10.1007/978-3-030-50146-4_19 https://doi.org/10.1007/978-3-030-50146-4_19 |
Resumo: | This work introduces a scheduling technique using the Artificial Bee Colony (ABC) algorithm for static and dynamic environments. The ABC algorithm combines different initial populations and generation of new food source methods, including a moving operations technique and a local search method increasing the variable neighbourhood search that, as a result, improves the solution quality. The algorithm is validated and its performance is tested in a static environment in 9 instances of Flexible Job Shop Problem (FJSP) from Brandimarte dataset obtaining in 5 instances the best known for the instance under study and a new best known in instance mk05. The work also focus in developing tools to process the information on the factory through the development of solutions when facing disruptions and dynamic events. Three real-time events are considered on the dynamic environment: jobs cancellation, operations cancellation and new jobs arrival. Two scenarios are studied for each real-time event: the first situation considers the minimization of the disruption between the previous schedule and the new one and the second situation generates a completely new schedule after the occurrence. Summarizing, six adaptations of ABC algorithm are created to solve dynamic environment scenarios and their performances are compared with the benchmarks of two case studies outperforming both. |
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Artificial Bee Colony Algorithm Applied to Dynamic Flexible Job Shop ProblemsDynamic environmentNew jobs arrivalOperations cancellationJobs cancellationFlexible job shop reschedulingThis work introduces a scheduling technique using the Artificial Bee Colony (ABC) algorithm for static and dynamic environments. The ABC algorithm combines different initial populations and generation of new food source methods, including a moving operations technique and a local search method increasing the variable neighbourhood search that, as a result, improves the solution quality. The algorithm is validated and its performance is tested in a static environment in 9 instances of Flexible Job Shop Problem (FJSP) from Brandimarte dataset obtaining in 5 instances the best known for the instance under study and a new best known in instance mk05. The work also focus in developing tools to process the information on the factory through the development of solutions when facing disruptions and dynamic events. Three real-time events are considered on the dynamic environment: jobs cancellation, operations cancellation and new jobs arrival. Two scenarios are studied for each real-time event: the first situation considers the minimization of the disruption between the previous schedule and the new one and the second situation generates a completely new schedule after the occurrence. Summarizing, six adaptations of ABC algorithm are created to solve dynamic environment scenarios and their performances are compared with the benchmarks of two case studies outperforming both.ELSEVIER2021-01-25T12:39:14Z2021-01-252020-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10174/28823https://doi.org/FERREIRA, I., FIRME, B., MARTINS, M., COITO, T., VIEGAS, J., FIGUEIREDO, J., VIEIRA, S. SOUSA, J. [2020] Artificial Bee Colony Algorithm Applied to Dynamic Flexible Job Shop Problems. In: Lesot MJ. et al. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2020. Communications in Computer and Information Science, vol 1237. Springer, Cham. https://doi.org/10.1007/978-3-030-50146-4_19https://doi.org/10.1007/978-3-030-50146-4_19http://hdl.handle.net/10174/28823https://doi.org/10.1007/978-3-030-50146-4_19porndndndndndjfig@uevora.ptndnd285Ferreira, I.Firme, B.Martins, M.Coito, T.Viegas, J.Figueiredo, JoaoVieira, S.Sousa, J.info: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:RCAAP2024-01-03T19:25:04Zoai:dspace.uevora.pt:10174/28823Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:18:29.525929Repositório 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 |
Artificial Bee Colony Algorithm Applied to Dynamic Flexible Job Shop Problems |
title |
Artificial Bee Colony Algorithm Applied to Dynamic Flexible Job Shop Problems |
spellingShingle |
Artificial Bee Colony Algorithm Applied to Dynamic Flexible Job Shop Problems Ferreira, I. Dynamic environment New jobs arrival Operations cancellation Jobs cancellation Flexible job shop rescheduling |
title_short |
Artificial Bee Colony Algorithm Applied to Dynamic Flexible Job Shop Problems |
title_full |
Artificial Bee Colony Algorithm Applied to Dynamic Flexible Job Shop Problems |
title_fullStr |
Artificial Bee Colony Algorithm Applied to Dynamic Flexible Job Shop Problems |
title_full_unstemmed |
Artificial Bee Colony Algorithm Applied to Dynamic Flexible Job Shop Problems |
title_sort |
Artificial Bee Colony Algorithm Applied to Dynamic Flexible Job Shop Problems |
author |
Ferreira, I. |
author_facet |
Ferreira, I. Firme, B. Martins, M. Coito, T. Viegas, J. Figueiredo, Joao Vieira, S. Sousa, J. |
author_role |
author |
author2 |
Firme, B. Martins, M. Coito, T. Viegas, J. Figueiredo, Joao Vieira, S. Sousa, J. |
author2_role |
author author author author author author author |
dc.contributor.author.fl_str_mv |
Ferreira, I. Firme, B. Martins, M. Coito, T. Viegas, J. Figueiredo, Joao Vieira, S. Sousa, J. |
dc.subject.por.fl_str_mv |
Dynamic environment New jobs arrival Operations cancellation Jobs cancellation Flexible job shop rescheduling |
topic |
Dynamic environment New jobs arrival Operations cancellation Jobs cancellation Flexible job shop rescheduling |
description |
This work introduces a scheduling technique using the Artificial Bee Colony (ABC) algorithm for static and dynamic environments. The ABC algorithm combines different initial populations and generation of new food source methods, including a moving operations technique and a local search method increasing the variable neighbourhood search that, as a result, improves the solution quality. The algorithm is validated and its performance is tested in a static environment in 9 instances of Flexible Job Shop Problem (FJSP) from Brandimarte dataset obtaining in 5 instances the best known for the instance under study and a new best known in instance mk05. The work also focus in developing tools to process the information on the factory through the development of solutions when facing disruptions and dynamic events. Three real-time events are considered on the dynamic environment: jobs cancellation, operations cancellation and new jobs arrival. Two scenarios are studied for each real-time event: the first situation considers the minimization of the disruption between the previous schedule and the new one and the second situation generates a completely new schedule after the occurrence. Summarizing, six adaptations of ABC algorithm are created to solve dynamic environment scenarios and their performances are compared with the benchmarks of two case studies outperforming both. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-01-01T00:00:00Z 2021-01-25T12:39:14Z 2021-01-25 |
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/10174/28823 https://doi.org/FERREIRA, I., FIRME, B., MARTINS, M., COITO, T., VIEGAS, J., FIGUEIREDO, J., VIEIRA, S. SOUSA, J. [2020] Artificial Bee Colony Algorithm Applied to Dynamic Flexible Job Shop Problems. In: Lesot MJ. et al. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2020. Communications in Computer and Information Science, vol 1237. Springer, Cham. https://doi.org/10.1007/978-3-030-50146-4_19 https://doi.org/10.1007/978-3-030-50146-4_19 http://hdl.handle.net/10174/28823 https://doi.org/10.1007/978-3-030-50146-4_19 |
url |
http://hdl.handle.net/10174/28823 https://doi.org/FERREIRA, I., FIRME, B., MARTINS, M., COITO, T., VIEGAS, J., FIGUEIREDO, J., VIEIRA, S. SOUSA, J. [2020] Artificial Bee Colony Algorithm Applied to Dynamic Flexible Job Shop Problems. In: Lesot MJ. et al. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2020. Communications in Computer and Information Science, vol 1237. Springer, Cham. https://doi.org/10.1007/978-3-030-50146-4_19 https://doi.org/10.1007/978-3-030-50146-4_19 |
dc.language.iso.fl_str_mv |
por |
language |
por |
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nd nd nd nd nd jfig@uevora.pt nd nd 285 |
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info:eu-repo/semantics/openAccess |
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openAccess |
dc.publisher.none.fl_str_mv |
ELSEVIER |
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ELSEVIER |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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