Perfomance evaluation of selection methods to solve the job shop scheduling problem

In evolutionary algorithms selection mechanisms aim to favour reproduction of better individuals imposing a direction on the search process. It does not create new individuals; instead it selects comparatively good individuals from a population and typically does it accorgind to their fitness. The i...

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Detalles Bibliográficos
Autores principales: Stark, Natalia, Salto, Carolina, Alfonso, Hugo, Gallard, Raúl Hector
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2002
Materias:
Ciencias Informáticas
Scheduling
performance
ARTIFICIAL INTELLIGENCE
selection
algorithms
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/22066
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-22066
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
Scheduling
performance
ARTIFICIAL INTELLIGENCE
selection
algorithms
spellingShingle Ciencias Informáticas
Scheduling
performance
ARTIFICIAL INTELLIGENCE
selection
algorithms
Stark, Natalia
Salto, Carolina
Alfonso, Hugo
Gallard, Raúl Hector
Perfomance evaluation of selection methods to solve the job shop scheduling problem
topic_facet Ciencias Informáticas
Scheduling
performance
ARTIFICIAL INTELLIGENCE
selection
algorithms
description In evolutionary algorithms selection mechanisms aim to favour reproduction of better individuals imposing a direction on the search process. It does not create new individuals; instead it selects comparatively good individuals from a population and typically does it accorgind to their fitness. The idea is that interacting with other individuals (competition), those with higher fitness have a higher probability to be selected for mating. In that manner, because the fitness of an individual gives a measure of its “goodness”, selection introduces the influence of the fitness function to the evolutionary process. Moreover, selection is the only operator of genetic algorithm where the fitness of an individual affects the evolution process. In such a process two important, strongly related, issues exist: selective pressure and population diversity. In this work we are showing the effect of applying different selection mechanisms to a set of instances of the Job Shop Scheduling Problem, with different degress of complexity. For these experiments we are using multiplicity features in the selection of parents for the reproduction with the possibility to generate multiple number of children too, because the results using these approaches outperform to those obtained under traditional evolutionary algorithms. This was shown in our previous works. A description of each method, experiments and preliminary results under different combinations are reported.
format Objeto de conferencia
Objeto de conferencia
author Stark, Natalia
Salto, Carolina
Alfonso, Hugo
Gallard, Raúl Hector
author_facet Stark, Natalia
Salto, Carolina
Alfonso, Hugo
Gallard, Raúl Hector
author_sort Stark, Natalia
title Perfomance evaluation of selection methods to solve the job shop scheduling problem
title_short Perfomance evaluation of selection methods to solve the job shop scheduling problem
title_full Perfomance evaluation of selection methods to solve the job shop scheduling problem
title_fullStr Perfomance evaluation of selection methods to solve the job shop scheduling problem
title_full_unstemmed Perfomance evaluation of selection methods to solve the job shop scheduling problem
title_sort perfomance evaluation of selection methods to solve the job shop scheduling problem
publishDate 2002
url http://sedici.unlp.edu.ar/handle/10915/22066
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AT saltocarolina perfomanceevaluationofselectionmethodstosolvethejobshopschedulingproblem
AT alfonsohugo perfomanceevaluationofselectionmethodstosolvethejobshopschedulingproblem
AT gallardraulhector perfomanceevaluationofselectionmethodstosolvethejobshopschedulingproblem
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