Hybridizing an immune artificial algorithm with simulated annealing for solving constrained optimization problems
In this paper, we present a modified version of an algorithm inspired on the T-Cell model, it is an artificial immune system (AIS), based on the process that suffers the T-Cell. The proposed model (TCSA) is increased with simulated annealing, for solving constrained (numerical) optimization problems...
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| Autores principales: | , , |
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| Formato: | Objeto de conferencia |
| Lenguaje: | Inglés |
| Publicado: |
2011
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| Materias: | |
| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/18623 |
| Aporte de: |
| Sumario: | In this paper, we present a modified version of an algorithm inspired on the T-Cell model, it is an artificial immune system (AIS), based on the process that suffers the T-Cell. The proposed model (TCSA) is increased with simulated annealing, for solving constrained (numerical) optimization problems. We validate our proposed approach with a set of test functions taken from the specialized literature. We indirectly compare our results with respect to GENOCOP III, a well known software based on genetic algorithm |
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