rmoo_Population: Population initialization in non-dominated genetic algorithms

In Evolutionary-Optimization-Laboratory/rmoo: Multi-Objective Optimization in R

Population initialization in non-dominated genetic algorithms

Description

Functions for creating a random initial population to be used in non-dominated genetic algorithms.

Usage

  rmoobin_Population(object)

  rmooreal_Population(object)

  rmooperm_Population(object)

Arguments

object

An object of class nsga-class, nsga2-class or nsga3-class.

Details

rmoobin_Population generates a random population of object@nBits binary values;

rmooreal_Population generates a random (uniform) population of real values in the range [object@lower, object@upper];

rmooperm_Population generates a random (uniform) population of integer values in the range [object@lower, object@upper].

Value

Return a matrix of dimension object@popSize times the number of decision variables.

Author(s)

Francisco Benitez

References

Scrucca, L. (2017) On some extensions to 'GA' package: hybrid optimisation, parallelisation and islands evolution. The R Journal, 9/1, 187-206, doi: 10.32614/RJ-2017-008.

See Also

nsga, nsga2 and nsga3

Evolutionary-Optimization-Laboratory/rmoo documentation built on Oct. 28, 2024, 5:45 p.m.