An ant colony optimization algorithm for job shop scheduling problem

The nature has inspired several metaheuristics, outstanding among these is Ant Colony Optimization (ACO), which have proved to be very effective and efficient in problems of high complexity (NP-hard) in combinatorial optimization. This paper describes the implementation of an ACO model algorithm kno...

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Detalles Bibliográficos
Autores principales: Flórez, Edson, Gómez, Wilfredo, Bautista, Lola
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2013
Materias:
Ciencias Informáticas
ant colony optimization
swarm intelligence
combinatorial optimization
job shop scheduling problem
Heuristic methods
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/76211
http://42jaiio.sadio.org.ar/proceedings/simposios/Trabajos/ASAI/07.pdf
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-76211
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
ant colony optimization
swarm intelligence
combinatorial optimization
job shop scheduling problem
Heuristic methods
spellingShingle Ciencias Informáticas
ant colony optimization
swarm intelligence
combinatorial optimization
job shop scheduling problem
Heuristic methods
Flórez, Edson
Gómez, Wilfredo
Bautista, Lola
An ant colony optimization algorithm for job shop scheduling problem
topic_facet Ciencias Informáticas
ant colony optimization
swarm intelligence
combinatorial optimization
job shop scheduling problem
Heuristic methods
description The nature has inspired several metaheuristics, outstanding among these is Ant Colony Optimization (ACO), which have proved to be very effective and efficient in problems of high complexity (NP-hard) in combinatorial optimization. This paper describes the implementation of an ACO model algorithm known as Elitist Ant System (EAS), applied to a combinatorial optimization problem called Job Shop Scheduling Problem (JSSP). We propose a method that seeks to reduce delays designating the operation immediately available, but considering the operations that lack little to be available and have a greater amount of pheromone. The performance of the algorithm was evaluated for problems of JSSP reference, comparing the quality of the solutions obtained regarding the best known solution of the most effective methods. The solutions were of good quality and obtained with a remarkable efficiency by having to make a very low number of objective function evaluations.
format Objeto de conferencia
Objeto de conferencia
author Flórez, Edson
Gómez, Wilfredo
Bautista, Lola
author_facet Flórez, Edson
Gómez, Wilfredo
Bautista, Lola
author_sort Flórez, Edson
title An ant colony optimization algorithm for job shop scheduling problem
title_short An ant colony optimization algorithm for job shop scheduling problem
title_full An ant colony optimization algorithm for job shop scheduling problem
title_fullStr An ant colony optimization algorithm for job shop scheduling problem
title_full_unstemmed An ant colony optimization algorithm for job shop scheduling problem
title_sort ant colony optimization algorithm for job shop scheduling problem
publishDate 2013
url http://sedici.unlp.edu.ar/handle/10915/76211
http://42jaiio.sadio.org.ar/proceedings/simposios/Trabajos/ASAI/07.pdf
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