Title :
Fixed, random or fuzzy adaptive parameters in an evolutionary algorithm
Author_Institution :
LIP6, Univ. Paris VI, Paris, France
Abstract :
Particular steady-state strategies of evolution with small sized population are studied in this paper. We specially focus our attention on the ways to reach a compromise with the best parameters, we observe improvements in order to optimize classical problems when using small populations and some clearing to make exploration directly connected to the homogeneity of the population We use for this fuzzy rules or random way to decide and move parameters.
Keywords :
evolutionary computation; fuzzy set theory; evolutionary algorithm; fixed parameters; fuzzy adaptive parameters; fuzzy rules; random parameters; steady-state strategies; Biological cells; Cities and towns; Evolution (biology); Evolutionary computation; Genetic algorithms; Genetics; Steady-state; evolutionary algorithms; fuzzy control; steady state genetic algorithms;
Conference_Titel :
Hybrid Intelligent Models And Applications (HIMA), 2011 IEEE Workshop On
Conference_Location :
Paris
Print_ISBN :
978-1-4244-9907-6
DOI :
10.1109/HIMA.2011.5953968