Methods for the edaSeed generic function.
edaSeedUniform(eda, lower, upper)Lower bounds of the variables of the objective function.
Upper bounds of the variables of the objective function.
A matrix with one column for each variable of the objective function and one row for each solution in the population.
Seeding methods create the initial population. The length of the lower
and upper vectors determine the number of variables of the objective
function. The following seeding methods are implemented.
edaSeedUniformSample each variable from a continuous uniform
distribution in the interval determined by lower and upper.
The parameter popSize sets the number of solutions in the population
(default value: 100). This is the default method of the
edaSeed generic function.
Gonzalez-Fernandez Y, Soto M (2014). copulaedas: An R Package for Estimation of Distribution Algorithms Based on Copulas. Journal of Statistical Software, 58(9), 1-34. http://www.jstatsoft.org/v58/i09/.