Abstract (EN):
Global optimization seeks a minimum or maximum of a multimodal function over a discrete or
continuous domain. In this paper, we propose a biased random-key genetic algorithm for finding
approximate solutions for continuous global optimization problems subject to box constraints. Experimental
results illustrate its effectiveness on the robot kinematics problem, a challenging problem
according to [7].
Idioma:
Inglês
Tipo (Avaliação Docente):
Científica
Contacto:
http://www.hpca.ual.es/~leo/gow/2012-XI-GOW.pdf
Tipo de Licença: