Evolutionary optimization in dynamic fitness landscape environments
Non-stationary, or dynamic, problems change over time. There exist a variety of forms of dynamism. The concept of dynamic environments in the context of this paper means that the fitness landscape changes during the run of an evolutionary algorithm. Genetic diversity is crucial to provide the neces...
Guardado en:
| Autores principales: | Aragón, Victoria S., Esquivel, Susana Cecilia |
|---|---|
| Formato: | Objeto de conferencia |
| Lenguaje: | Inglés |
| Publicado: |
2003
|
| Materias: | |
| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/22732 |
| Aporte de: |
Ejemplares similares
-
Optimization of tardiness related objectives in single machine environments via multirecombined evolutionary algorithms
por: San Pedro, María Eugenia de, et al.
Publicado: (2003) -
Upgrading evolutionary algorithms through multiplicity for multiobjective optimization in job shop scheduling problems
por: Esquivel, Susana Cecilia, et al.
Publicado: (2001) -
Evolutionaty algorithms with clustering for dynamic fitness landscapes
por: Esquivel, Susana Cecilia, et al.
Publicado: (2005) -
Evolutionary multiobjetive optimization in non-stationary environments
por: Aragón, Victoria S., et al.
Publicado: (2005) -
A comparison of fitness scallng methods in evolutionary algorithms
por: Bertone, E., et al.
Publicado: (1999)