edaSeed: Seeding Methods
In copulaedas: Estimation of Distribution Algorithms Based on Copulas

Description Usage Arguments Details Value References

Methods for the edaSeed generic function.

1	edaSeedUniform(eda, lower, upper)

`eda`	`EDA` instance.
`lower`	Lower bounds of the variables of the objective function.
`upper`	Upper bounds of the variables of the objective function.

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.

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

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/.

copulaedas documentation built on May 1, 2019, 10:24 p.m.