info:eu-repo/semantics/article
Evolutionary algorithms with clustering for dynamic fitness landscapes
Fecha
2005-12Registro en:
Aragon, Victoria Soledad; Esquivel, Susana Cecilia; Evolutionary algorithms with clustering for dynamic fitness landscapes; Universidad Nacional de La Plata. Facultad de Informática; Journal of Computer Science & Technology; 5; 4; 12-2005; 196-203
1666-6046
1666-6038
CONICET Digital
CONICET
Autor
Aragon, Victoria Soledad
Esquivel, Susana Cecilia
Resumen
Interest on dynamic multimodal functions risen over the last years since many real problems have this feature. On these problems, the goal is no longer to find the global optimal, but to track their progression through the space as closely as possible. This paper presents three evolutionary algorithms for dynamic fitness landscapes. In order to mantain diversity in the population they use two clustering techniques and a macromutation operator. Besides, this paper compares two crossover operators: arithmetic and multiparents two points, respectively. Effectiveness and limitations of each algorithm are discuss and analyzed.