Optimizing constrained problems through a T-Cell artificial immune system
In this paper, we present a new model of an artificial immune system (AIS), based on the process that suffers the T-Cell, it is called T-Cell Model. It is used for solving constrained (numerical) optimization problems. The model operates on three populations: Virgins, Effectors and Memory. Each of t...
Guardado en:
| Autores principales: | , , |
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| Formato: | Articulo |
| Lenguaje: | Inglés |
| Publicado: |
2008
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| Materias: | |
| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/9640 http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Oct08-5.pdf |
| Aporte de: |
| id |
I19-R120-10915-9640 |
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| 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 artificial immune system constrained optimization problem |
| spellingShingle |
Ciencias Informáticas artificial immune system constrained optimization problem Aragón, Victoria S. Esquivel, Susana Cecilia Coello Coello, Carlos Optimizing constrained problems through a T-Cell artificial immune system |
| topic_facet |
Ciencias Informáticas artificial immune system constrained optimization problem |
| description |
In this paper, we present a new model of an artificial immune system (AIS), based on the process that suffers the T-Cell, it is called T-Cell Model. It is used for solving constrained (numerical) optimization problems. The model operates on three populations: Virgins, Effectors and Memory. Each of them has a different role. Also, the model dynamically adapts the tolerance factor in order to improve the exploration capabilities of the algorithm. We also develop a new mutation operator which incorporates knowledge of the problem. We validate our proposed approach with a set of test functions taken from the specialized literature and we compare our results with respect to Stochastic Ranking (which is an approach representative of the state-of-theart in the area), with respect to an AIS previously proposed and a self-organizing migrating genetic algorithm for constrained optimization (C-SOMGA). |
| format |
Articulo Articulo |
| author |
Aragón, Victoria S. Esquivel, Susana Cecilia Coello Coello, Carlos |
| author_facet |
Aragón, Victoria S. Esquivel, Susana Cecilia Coello Coello, Carlos |
| author_sort |
Aragón, Victoria S. |
| title |
Optimizing constrained problems through a T-Cell artificial immune system |
| title_short |
Optimizing constrained problems through a T-Cell artificial immune system |
| title_full |
Optimizing constrained problems through a T-Cell artificial immune system |
| title_fullStr |
Optimizing constrained problems through a T-Cell artificial immune system |
| title_full_unstemmed |
Optimizing constrained problems through a T-Cell artificial immune system |
| title_sort |
optimizing constrained problems through a t-cell artificial immune system |
| publishDate |
2008 |
| url |
http://sedici.unlp.edu.ar/handle/10915/9640 http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Oct08-5.pdf |
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AT aragonvictorias optimizingconstrainedproblemsthroughatcellartificialimmunesystem AT esquivelsusanacecilia optimizingconstrainedproblemsthroughatcellartificialimmunesystem AT coellocoellocarlos optimizingconstrainedproblemsthroughatcellartificialimmunesystem |
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Repositorios |
| _version_ |
1764820492087197700 |