rmoo_Mutation: Mutation operators in non-dominated genetic algorithms

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

Mutation operators in non-dominated genetic algorithms

Description

Functions implementing mutation non-dominated genetic operator.

Usage

  rmoobin_raMutation(object, parent)

  rmooreal_raMutation(object, parent)
  rmooreal_polMutation(object, parent, eta = 20, indpb = 0.5)

  rmooperm_simMutation(object, parent)

Arguments

object	An object of class "nsga", "nsga2" or "nsga3" usually resulting from a call to function nsga, nsga2, nsga3.
parent	A vector of values for the parent from the current population where mutation should occur.
eta	Distribution parameter for mutation operator.
indpb	Independent mutation probability.

Value

Return a vector of values containing the mutated string.

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.

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