MCPC: another approach to crossover in genetic algorithms
Genetic algorithms (GAs) are stochastic adaptive algorithms whose search method is based on simulation of natural genetic inheritance and Darwinian strive for survival. They can be used to find approximate solutions to numerical optimization problems in cases where finding the exact optimum is prohi...
Guardado en:
Autores principales: | Esquivel, Susana Cecilia, Gallard, Raúl Hector, Michalewicz, Zbigniew |
---|---|
Formato: | Objeto de conferencia |
Lenguaje: | Inglés |
Publicado: |
1995
|
Materias: | |
Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/24282 |
Aporte de: |
Ejemplares similares
-
Self-adaptation of parameters for MCPC in genetic algorithms
por: Esquivel, Susana Cecilia, et al.
Publicado: (1998) -
Self adaptation of parameters for MCPC in genetic algorithms
por: Esquivel, Susana Cecilia, et al.
Publicado: (2000) -
Multiple crossover per couple and fitness proportional couple selection in genetic algorithms
por: Esquivel, Susana Cecilia, et al.
Publicado: (1997) -
A study of alternative selection mechanisms for multiple cossover per couple in genetic algorithms
por: Esquivel, Susana Cecilia, et al.
Publicado: (1998) -
Influence of crossover operators in evolutionary scheduling under multirecombined schemes
por: San Pedro, María Eugenia de, et al.
Publicado: (2003)