2016 | OriginalPaper | Buchkapitel
Performance Evaluation of the Genetic Landscape Evolution (GLE) Model with Respect to Crossover Schemes
verfasst von : JongChun Kim, Kyungrock Paik
Erschienen in: Harmony Search Algorithm
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
We investigate performance of the Genetic Landscape Evolution (GLE) model by changing number of crossover points, which controls spatial cohesiveness of topological information in generated offspring. Simulation results show that 1) GLE performance is insensitive to the number of crossover points, implying that the spatial cohesiveness does not significantly affect efficiency to find better solution sets; and 2) the method to generate randomness in GLE is a significant element for its performance.