Comparison of Different Approaches for Adapting Mutation Probabilities in Genetic Algorithms
Traditionally in Genetic Algorithms, the mutation probability parameter maintains a constant value during the search. However, an important difficulty is to determine a priori which probability value is the best suited for a given problem. In this paper we compare three different adaptive algorithms...
Guardado en:
| Autores principales: | Stark, Natalia, Minetti, Gabriela F., Salto, Carolina |
|---|---|
| Formato: | Objeto de conferencia |
| Lenguaje: | Inglés |
| Publicado: |
2016
|
| Materias: | |
| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/55739 |
| Aporte de: |
Ejemplares similares
-
A new strategy for adapting the mutation probability in genetic algorithms
por: Stark, Natalia, et al.
Publicado: (2012) -
Self adaptation of parameters for MCPC in genetic algorithms
por: Esquivel, Susana Cecilia, et al.
Publicado: (2000) -
A general framework to understand parallel performance in heterogeneous clusters: Analysis of a new adaptive parallel genetic algorithm
por: Bazterra, V.E., et al. -
A general framework to understand parallel performance in heterogeneous clusters: Analysis of a new adaptive parallel genetic algorithm
por: Bazterra, Víctor Eduardo, et al.
Publicado: (2005) -
Self-adaptation of parameters for MCPC in genetic algorithms
por: Esquivel, Susana Cecilia, et al.
Publicado: (1998)