An improved ant colony algorithm for the job shop scheduling problem

Instances of static scheduling problems can be easily represented as graphs where each node represents a particular operation. This property makes the Ant Colony Algorithms well suited for different kinds of scheduling problems. In this paper we present an improved Ant System for solving the Job Sho...

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Detalles Bibliográficos
Autores principales: Leguizamón, Guillermo, Schutz, Martín
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2002
Materias:
Ciencias Informáticas
ant colony optimization
job shop scheduling problem
active and non-delay schedules
Optimization
Scheduling
ARTIFICIAL INTELLIGENCE
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/23004
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-23004
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
job shop scheduling problem
active and non-delay schedules
Optimization
Scheduling
ARTIFICIAL INTELLIGENCE
spellingShingle Ciencias Informáticas
ant colony optimization
job shop scheduling problem
active and non-delay schedules
Optimization
Scheduling
ARTIFICIAL INTELLIGENCE
Leguizamón, Guillermo
Schutz, Martín
An improved ant colony algorithm for the job shop scheduling problem
topic_facet Ciencias Informáticas
ant colony optimization
job shop scheduling problem
active and non-delay schedules
Optimization
Scheduling
ARTIFICIAL INTELLIGENCE
description Instances of static scheduling problems can be easily represented as graphs where each node represents a particular operation. This property makes the Ant Colony Algorithms well suited for different kinds of scheduling problems. In this paper we present an improved Ant System for solving the Job Shop Scheduling (JSS) Problem. After each cycle the Ant System applies a scheduler builder to each solution. The schedule builder is able to generate under a controlled manner different types of schedules (from non-delay to active). Any improvement achieved for a solution will affect the performance of the algorithm in the next cycles by changing accordingly the amount of pheromone on certain paths. Since the pheromone is the building block of an ant algorithm, it is expected that these changes guide the search towards more promising areas of the search space. The computational study involves a set of instances of different size and difficulty. The results are compared against the best solutions known so far and results reported from earlier studies of ant algorithms applied to the JSSP.
format Objeto de conferencia
Objeto de conferencia
author Leguizamón, Guillermo
Schutz, Martín
author_facet Leguizamón, Guillermo
Schutz, Martín
author_sort Leguizamón, Guillermo
title An improved ant colony algorithm for the job shop scheduling problem
title_short An improved ant colony algorithm for the job shop scheduling problem
title_full An improved ant colony algorithm for the job shop scheduling problem
title_fullStr An improved ant colony algorithm for the job shop scheduling problem
title_full_unstemmed An improved ant colony algorithm for the job shop scheduling problem
title_sort improved ant colony algorithm for the job shop scheduling problem
publishDate 2002
url http://sedici.unlp.edu.ar/handle/10915/23004
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AT schutzmartin animprovedantcolonyalgorithmforthejobshopschedulingproblem
AT leguizamonguillermo improvedantcolonyalgorithmforthejobshopschedulingproblem
AT schutzmartin improvedantcolonyalgorithmforthejobshopschedulingproblem
bdutipo_str Repositorios
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