Optimization of the control parameters of genetic algorithms is often a time consuming and tedious task. In this work we take the meta-level genetic algorithm approach to control ...
In this work we examined the performance of two evolutionary algorithms, a genetic algorithm (GA) and particle swarm optimization (PSO), in the estimation of the parameters of a mo...
Dulce Calcada, Agostinho Rosa, Luis C. Duarte, Vit...
A meta-GA (GA within a GA) is used to investigate evolving the parameter settings of genetic operators for genetic and evolutionary algorithms (GEA) in the hope of creating a self...
Jeff Clune, Sherri Goings, Bill Punch, Eric Goodma...
Crop Assimilation Model (CAM) predicts the parameters of agrohydrological models with satellite images. CAM with double layers GA called CAM-DLGA, uses Soil-Water-Atmosphere-Plant ...
We show how and why using genetic operators that are applied with probabilities that depend on the fitness rank of a genotype or phenotype offers a robust alternative to the Sim...