edaSeed {copulaedas}

Seeding Methods

Description

Methods for the edaSeed generic function.

Usage

edaSeedUniform(eda, lower, upper)

Arguments

eda

EDA instance.

lower

Lower bounds of the variables of the objective function.

upper

Upper bounds of the variables of the objective function.

Details

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.

edaSeedUniform

Sample 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.

Value

A matrix with one column for each variable of the objective function and one row for each solution in the population.

References

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/.