A Simple Differential Evolution Algorithm to Solve the Flexible Job Shop Scheduling Problem
- Autores
- Morero, Franco; Bermúdez, Carlos; Salto, Carolina
- Año de publicación
- 2019
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- This paper addresses the Flexible Job Shop Scheduling Problem (FJSSP) where the objective is to minimize the makespan. We develop a parallel hybrid Differential Evolution (DE) algorithm to tackle this problem. A random key representation of the FJSSP is adopted, which requires a very simple conversion mechanism to obtain a feasible schedule. This allows the DE algorithm to work on the continuous domain to explore the problem space of the discrete FJSSP. Moreover, a simple local search algorithm is embedded in the DE framework to balance the exploration and exploitation by enhancing the local searching ability. In addition, parallelism of the DE operations is included to improve the efficiency of whole algorithm. Experiments confirm the significant improvement achieved by integrating the propositions introduced in this study. Additional, test results show that our algorithm is competitive when compared with most existing approaches for the FJSSP.
XX Workshop Agentes y Sistemas Inteligentes.
Red de Universidades con Carreras en Informática - Materia
-
Ciencias Informáticas
Flexible job shop scheduling
Differential evolution algorithm - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/4.0/
- Repositorio
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/90890
Ver los metadatos del registro completo
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A Simple Differential Evolution Algorithm to Solve the Flexible Job Shop Scheduling ProblemMorero, FrancoBermúdez, CarlosSalto, CarolinaCiencias InformáticasFlexible job shop schedulingDifferential evolution algorithmThis paper addresses the Flexible Job Shop Scheduling Problem (FJSSP) where the objective is to minimize the makespan. We develop a parallel hybrid Differential Evolution (DE) algorithm to tackle this problem. A random key representation of the FJSSP is adopted, which requires a very simple conversion mechanism to obtain a feasible schedule. This allows the DE algorithm to work on the continuous domain to explore the problem space of the discrete FJSSP. Moreover, a simple local search algorithm is embedded in the DE framework to balance the exploration and exploitation by enhancing the local searching ability. In addition, parallelism of the DE operations is included to improve the efficiency of whole algorithm. Experiments confirm the significant improvement achieved by integrating the propositions introduced in this study. Additional, test results show that our algorithm is competitive when compared with most existing approaches for the FJSSP.XX Workshop Agentes y Sistemas Inteligentes.Red de Universidades con Carreras en Informática2019-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf2-11http://sedici.unlp.edu.ar/handle/10915/90890enginfo:eu-repo/semantics/altIdentifier/isbn/978-987-688-377-1info:eu-repo/semantics/reference/hdl/10915/90359info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-03T10:51:17Zoai:sedici.unlp.edu.ar:10915/90890Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 10:51:17.859SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
A Simple Differential Evolution Algorithm to Solve the Flexible Job Shop Scheduling Problem |
title |
A Simple Differential Evolution Algorithm to Solve the Flexible Job Shop Scheduling Problem |
spellingShingle |
A Simple Differential Evolution Algorithm to Solve the Flexible Job Shop Scheduling Problem Morero, Franco Ciencias Informáticas Flexible job shop scheduling Differential evolution algorithm |
title_short |
A Simple Differential Evolution Algorithm to Solve the Flexible Job Shop Scheduling Problem |
title_full |
A Simple Differential Evolution Algorithm to Solve the Flexible Job Shop Scheduling Problem |
title_fullStr |
A Simple Differential Evolution Algorithm to Solve the Flexible Job Shop Scheduling Problem |
title_full_unstemmed |
A Simple Differential Evolution Algorithm to Solve the Flexible Job Shop Scheduling Problem |
title_sort |
A Simple Differential Evolution Algorithm to Solve the Flexible Job Shop Scheduling Problem |
dc.creator.none.fl_str_mv |
Morero, Franco Bermúdez, Carlos Salto, Carolina |
author |
Morero, Franco |
author_facet |
Morero, Franco Bermúdez, Carlos Salto, Carolina |
author_role |
author |
author2 |
Bermúdez, Carlos Salto, Carolina |
author2_role |
author author |
dc.subject.none.fl_str_mv |
Ciencias Informáticas Flexible job shop scheduling Differential evolution algorithm |
topic |
Ciencias Informáticas Flexible job shop scheduling Differential evolution algorithm |
dc.description.none.fl_txt_mv |
This paper addresses the Flexible Job Shop Scheduling Problem (FJSSP) where the objective is to minimize the makespan. We develop a parallel hybrid Differential Evolution (DE) algorithm to tackle this problem. A random key representation of the FJSSP is adopted, which requires a very simple conversion mechanism to obtain a feasible schedule. This allows the DE algorithm to work on the continuous domain to explore the problem space of the discrete FJSSP. Moreover, a simple local search algorithm is embedded in the DE framework to balance the exploration and exploitation by enhancing the local searching ability. In addition, parallelism of the DE operations is included to improve the efficiency of whole algorithm. Experiments confirm the significant improvement achieved by integrating the propositions introduced in this study. Additional, test results show that our algorithm is competitive when compared with most existing approaches for the FJSSP. XX Workshop Agentes y Sistemas Inteligentes. Red de Universidades con Carreras en Informática |
description |
This paper addresses the Flexible Job Shop Scheduling Problem (FJSSP) where the objective is to minimize the makespan. We develop a parallel hybrid Differential Evolution (DE) algorithm to tackle this problem. A random key representation of the FJSSP is adopted, which requires a very simple conversion mechanism to obtain a feasible schedule. This allows the DE algorithm to work on the continuous domain to explore the problem space of the discrete FJSSP. Moreover, a simple local search algorithm is embedded in the DE framework to balance the exploration and exploitation by enhancing the local searching ability. In addition, parallelism of the DE operations is included to improve the efficiency of whole algorithm. Experiments confirm the significant improvement achieved by integrating the propositions introduced in this study. Additional, test results show that our algorithm is competitive when compared with most existing approaches for the FJSSP. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-10 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion Objeto de conferencia http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
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conferenceObject |
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publishedVersion |
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http://sedici.unlp.edu.ar/handle/10915/90890 |
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dc.language.none.fl_str_mv |
eng |
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eng |
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info:eu-repo/semantics/altIdentifier/isbn/978-987-688-377-1 info:eu-repo/semantics/reference/hdl/10915/90359 |
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info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
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openAccess |
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http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) |
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application/pdf 2-11 |
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