A criteria to select genetic operators for solving CSP

A criteria to select genetic operators for solving CSP

Our interest is to define evolutionary algorithms to solve Constraint Satisfaction Problems (CSP), which indlude benefits of taditional resolution methods of CSPs as well as inherent characteristics of these kind of problems. In this paper we propose a criterion to be able to evaluate the perfomance...

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Main Author: María Cristina Riff Rojas
Format: Article
Language:English
Published: Postgraduate Office, School of Computer Science, Universidad Nacional de La Plata 2000-03-01
Series:Journal of Computer Science and Technology
Subjects:
evolutionary algorithms
constraint satisfaction
specialized genetic operators
Online Access:https://journal.info.unlp.edu.ar/JCST/article/view/1013
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spelling doaj-bc9d1a963fb64fd79e9076c408f66a502021-05-05T14:41:19ZengPostgraduate Office, School of Computer Science, Universidad Nacional de La PlataJournal of Computer Science and Technology1666-60461666-60382000-03-0110213 p.13 p.706A criteria to select genetic operators for solving CSPMaría Cristina Riff Rojas0Universidad Técnica Federico Santa María, Valparaíso, ChileOur interest is to define evolutionary algorithms to solve Constraint Satisfaction Problems (CSP), which indlude benefits of taditional resolution methods of CSPs as well as inherent characteristics of these kind of problems. In this paper we propose a criterion to be able to evaluate the perfomance of genetic operators within evolutionary algorithms that solve CSp.https://journal.info.unlp.edu.ar/JCST/article/view/1013evolutionary algorithmsconstraint satisfactionspecialized genetic operators
collection DOAJ
language English
format Article
sources DOAJ
author María Cristina Riff Rojas
spellingShingle María Cristina Riff Rojas
A criteria to select genetic operators for solving CSP
Journal of Computer Science and Technology
evolutionary algorithms
constraint satisfaction
specialized genetic operators
author_facet María Cristina Riff Rojas
author_sort María Cristina Riff Rojas
title A criteria to select genetic operators for solving CSP
title_short A criteria to select genetic operators for solving CSP
title_full A criteria to select genetic operators for solving CSP
title_fullStr A criteria to select genetic operators for solving CSP
title_full_unstemmed A criteria to select genetic operators for solving CSP
title_sort criteria to select genetic operators for solving csp
publisher Postgraduate Office, School of Computer Science, Universidad Nacional de La Plata
series Journal of Computer Science and Technology
issn 1666-6046
1666-6038
publishDate 2000-03-01
description Our interest is to define evolutionary algorithms to solve Constraint Satisfaction Problems (CSP), which indlude benefits of taditional resolution methods of CSPs as well as inherent characteristics of these kind of problems. In this paper we propose a criterion to be able to evaluate the perfomance of genetic operators within evolutionary algorithms that solve CSp.
topic evolutionary algorithms
constraint satisfaction
specialized genetic operators
url https://journal.info.unlp.edu.ar/JCST/article/view/1013
work_keys_str_mv AT mariacristinariffrojas acriteriatoselectgeneticoperatorsforsolvingcsp
AT mariacristinariffrojas criteriatoselectgeneticoperatorsforsolvingcsp
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