A hybrid method to optimize the Flexible Job Shop Scheduling Problem

This article addresses task scheduling in the Flexible Job Shop Scheduling Problem (FJSSP). In this manufacturing system, it is necessary to intensify the number of jobs to be processed due to the current conditions of the industrial sector where there is an increase in the demand for products, whic...

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Autores: Escamilla-Serna, Nayeli J., Seck-Tuoh-Mora, Juan C., Medina-Marín, Joselito, Barragan-Vite, Irving, Corona-Armenta, José R.
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2022
País:México
Recursos:UNIVERSIDAD AUTÓNOMA DEL ESTADO DE HIDALGO
Repositorio:PÄDI Boletín Científico de Ciencias Básicas e Ingeniería del ICBI
Idioma:español
OAI Identifier:oai:repository.uaeh.edu.mx:article/8651
Acesso em linha:https://repository.uaeh.edu.mx/revistas/index.php/icbi/article/view/8651
Access Level:acceso abierto
Palavra-chave:• Flexible Job Shop Scheduling Problem
genetic algorithms
hill climbing
hybrid optimization
makespan
algoritmos genéticos
escalada de colina
optimización híbrida
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spelling A hybrid method to optimize the Flexible Job Shop Scheduling ProblemMétodo híbrido para optimizar el Flexible Job Shop Scheduling ProblemEscamilla-Serna, Nayeli J.Seck-Tuoh-Mora, Juan C.Medina-Marín, JoselitoBarragan-Vite, IrvingCorona-Armenta, José R.• Flexible Job Shop Scheduling Problemgenetic algorithmshill climbinghybrid optimizationmakespan• Flexible Job Shop Scheduling Problemalgoritmos genéticosescalada de colinaoptimización híbridaThis article addresses task scheduling in the Flexible Job Shop Scheduling Problem (FJSSP). In this manufacturing system, it is necessary to intensify the number of jobs to be processed due to the current conditions of the industrial sector where there is an increase in the demand for products, which leads to an increase in production. To find a task schedule close to the optimum. A hybrid optimization method is proposed using a global search based on genetic algorithms (GA) that have good diversification. A restart hill-climbing process (RHC) is used as a local search method in order to improve each solution. These metaheuristics yield the equilibrium necessary to find the best solution that minimizes the makespan as a cost function. The proposed algorithm was implemented in Matlab, and the results were compared with recently published research to review its efficiency.Este artículo aborda la programación de tareas en el Flexible Job Shop Scheduling Problem (FJSSP). En este sistema de manufactura es necesario incrementar el número de trabajos a procesar debido a las condiciones actuales del sector industrial en donde existe un aumento en la demanda de productos, lo que conlleva a incrementar la producción. Para encontrar una programación de tareas cercana al óptimo. Se propone un método de optimización híbrida utilizando una búsqueda global basada en algoritmos genéticos (AG) que tienen buena diversificación y para la búsqueda local se aplica una escalada de colinas simple con reinicio (ECR) para mejorar cada solución. La combinación de estas metaheurísticas obtiene el equilibrio necesario para encontrar la mejor programación de tareas con el fin de minimizar el makespan como función costo. Se implementó el algoritmo propuesto en Matlab, para comprobar su eficiencia se compararon los resultados con investigaciones recientemente publicadas.Universidad Autónoma del Estado de Hidalgo2022-06-24info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://repository.uaeh.edu.mx/revistas/index.php/icbi/article/view/865110.29057/icbi.v10iEspecial2.8651Pädi Boletín Científico de Ciencias Básicas e Ingenierías del ICBI; Vol 10 No Especial2 (2022): Pädi Boletín Científico de Ciencias Básicas e Ingenierías del ICBI; 56-64Pädi Boletín Científico de Ciencias Básicas e Ingenierías del ICBI; Vol. 10 Núm. Especial2 (2022): Pädi Boletín Científico de Ciencias Básicas e Ingenierías del ICBI; 56-642007-636310.29057/icbi.v10iEspecial2reponame:PÄDI Boletín Científico de Ciencias Básicas e Ingeniería del ICBIinstname:UNIVERSIDAD AUTÓNOMA DEL ESTADO DE HIDALGOinstacron:UAEHspahttps://repository.uaeh.edu.mx/revistas/index.php/icbi/article/view/8651/9011info:eu-repo/semantics/openAccessoai:repository.uaeh.edu.mx:article/86512024-08-19T22:36:44Z
dc.title.none.fl_str_mv A hybrid method to optimize the Flexible Job Shop Scheduling Problem
Método híbrido para optimizar el Flexible Job Shop Scheduling Problem
title A hybrid method to optimize the Flexible Job Shop Scheduling Problem
spellingShingle A hybrid method to optimize the Flexible Job Shop Scheduling Problem
Escamilla-Serna, Nayeli J.
• Flexible Job Shop Scheduling Problem
genetic algorithms
hill climbing
hybrid optimization
makespan
• Flexible Job Shop Scheduling Problem
algoritmos genéticos
escalada de colina
optimización híbrida
title_short A hybrid method to optimize the Flexible Job Shop Scheduling Problem
title_full A hybrid method to optimize the Flexible Job Shop Scheduling Problem
title_fullStr A hybrid method to optimize the Flexible Job Shop Scheduling Problem
title_full_unstemmed A hybrid method to optimize the Flexible Job Shop Scheduling Problem
title_sort A hybrid method to optimize the Flexible Job Shop Scheduling Problem
dc.creator.none.fl_str_mv Escamilla-Serna, Nayeli J.
Seck-Tuoh-Mora, Juan C.
Medina-Marín, Joselito
Barragan-Vite, Irving
Corona-Armenta, José R.
author Escamilla-Serna, Nayeli J.
author_facet Escamilla-Serna, Nayeli J.
Seck-Tuoh-Mora, Juan C.
Medina-Marín, Joselito
Barragan-Vite, Irving
Corona-Armenta, José R.
author_role author
author2 Seck-Tuoh-Mora, Juan C.
Medina-Marín, Joselito
Barragan-Vite, Irving
Corona-Armenta, José R.
author2_role author
author
author
author
dc.subject.none.fl_str_mv • Flexible Job Shop Scheduling Problem
genetic algorithms
hill climbing
hybrid optimization
makespan
• Flexible Job Shop Scheduling Problem
algoritmos genéticos
escalada de colina
optimización híbrida
topic • Flexible Job Shop Scheduling Problem
genetic algorithms
hill climbing
hybrid optimization
makespan
• Flexible Job Shop Scheduling Problem
algoritmos genéticos
escalada de colina
optimización híbrida
description This article addresses task scheduling in the Flexible Job Shop Scheduling Problem (FJSSP). In this manufacturing system, it is necessary to intensify the number of jobs to be processed due to the current conditions of the industrial sector where there is an increase in the demand for products, which leads to an increase in production. To find a task schedule close to the optimum. A hybrid optimization method is proposed using a global search based on genetic algorithms (GA) that have good diversification. A restart hill-climbing process (RHC) is used as a local search method in order to improve each solution. These metaheuristics yield the equilibrium necessary to find the best solution that minimizes the makespan as a cost function. The proposed algorithm was implemented in Matlab, and the results were compared with recently published research to review its efficiency.
publishDate 2022
dc.date.none.fl_str_mv 2022-06-24
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://repository.uaeh.edu.mx/revistas/index.php/icbi/article/view/8651
10.29057/icbi.v10iEspecial2.8651
url https://repository.uaeh.edu.mx/revistas/index.php/icbi/article/view/8651
identifier_str_mv 10.29057/icbi.v10iEspecial2.8651
dc.language.none.fl_str_mv spa
language spa
dc.relation.none.fl_str_mv https://repository.uaeh.edu.mx/revistas/index.php/icbi/article/view/8651/9011
dc.rights.none.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 Universidad Autónoma del Estado de Hidalgo
publisher.none.fl_str_mv Universidad Autónoma del Estado de Hidalgo
dc.source.none.fl_str_mv Pädi Boletín Científico de Ciencias Básicas e Ingenierías del ICBI; Vol 10 No Especial2 (2022): Pädi Boletín Científico de Ciencias Básicas e Ingenierías del ICBI; 56-64
Pädi Boletín Científico de Ciencias Básicas e Ingenierías del ICBI; Vol. 10 Núm. Especial2 (2022): Pädi Boletín Científico de Ciencias Básicas e Ingenierías del ICBI; 56-64
2007-6363
10.29057/icbi.v10iEspecial2
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instacron_str UAEH
institution UAEH
reponame_str PÄDI Boletín Científico de Ciencias Básicas e Ingeniería del ICBI
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