rmoo_Selection: Selection operators in non-dominated genetic algorithms

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

Selection operators in non-dominated genetic algorithms

Description

Functions implementing selection non-dominated genetic operator.

Usage

  rmoo_lrSelection(object, r, q)
  rmoo_tourSelection(object, k = 2, ...)

  rmoobin_lrSelection(object, r, q)
  rmoobin_tourSelection(object, k = 2, ...)

  rmooreal_lrSelection(object, r, q)
  rmooreal_tourSelection(object, k = 2, ...)

  rmooperm_lrSelection(object, r, q)
  rmooperm_tourSelection(object, k = 2, ...)

Arguments

object	An object of class "nsga", "nsga2" or "nsga3", usually resulting from a call to function nsga, nsga2 or nsga3.
r	A tuning parameter for the specific selection operator.
q	A tuning parameter for the specific selection operator.
k	A tuning parameter for the specific selection operator.
...	Further arguments passed to or from other methods.

Value

Return a list with two elements:

population	a matrix of dimension object@popSize times the number of decision variables containing the selected individuals or strings;
fitness	a vector of length object@popSize containing the fitness values for the selected individuals.

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.