Anzeige
Erschienen in:
2005 | OriginalPaper | Buchkapitel
Applying the Clonal Selection Principle to Find Flexible Job-Shop Schedules
verfasst von : Z. X. Ong, J. C. Tay, C. K. Kwoh
Erschienen in: Artificial Immune Systems
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 apply the Clonal Selection principle of the human immune system to solve the Flexible Job-Shop Problem with recirculation. Various practical design issues are addressed in the implemented algorithm, ClonaFLEX; first, an efficient antibody representation which creates only feasible solutions and a bootstrapping antibody initialization method to reduce the search time required. Second, the assignment of suitable mutation rates for antibodies based on their affinity. To this end, a simple yet effective visual method of determining the optimal mutation value is proposed. And third, to prevent premature convergence, a novel way of using elite pools to incubate antibodies is presented. Performance results of ClonaFLEX are obtained against benchmark FJSP instances by Kacem and Brandimarte. On average, ClonaFLEX outperforms a cultural evolutionary algorithm (EA) in 7 out of 12 problem sets, equivalent results for 4 and poorer in 1.