Description Usage Arguments Value Author(s) References Examples

A fast and elitist multiobjective genetic algorithm based on R.

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`fn` |
Objective functions to be minimized |

`varNo` |
Number of decision variables |

`objDim` |
Number of objective functions |

`lowerBounds` |
Lower bounds of each decision variable |

`upperBounds` |
Upper bounds of each decision variable |

`popSize` |
Size of population |

`tourSize` |
Size of tournament |

`generations` |
Number of generations |

`cprob` |
Crossover probability |

`XoverDistIdx` |
Crossover distribution index, it can be any nonnegative real number |

`mprob` |
Mutation probability |

`MuDistIdx` |
Mutation distribution index, it can be any nonnegative real number |

The returned value is a 'nsga2R' object with the following fields in additional to above NSGA-II settings:

`parameters` |
Solutions of decision variables found |

`objectives` |
Non-dominated objective function values |

`paretoFrontRank` |
Nondomination ranks (or levels) that each non-dominated solution belongs to |

`crowdingDistance` |
Crowding distance of each non-dominated solution |

Ching-Shih (Vince) Tsou cst[email protected]

Deb, K., Pratap, A., Agarwal, S., and Meyarivan, T. (2002), " A fast and elitist multiobjective genetic algorithm: NSGA-II", *IEEE Transactions on Evolutionary Computation*, **6(2)**, 182-197.

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