In EDO, as in EO, an algorithm is a functor that takes one or several solutions to an optimization problem as arguments, and iteratively modify them with the help of operators.It differs from a canonical EO algorithm because it is templatized on a edoDistrib rather than just an EOT. More...

## Classes | |

class | edoAlgo< D > |

An EDO algorithm differs from a canonical EO algorithm because it is templatized on a Distribution rather than just an EOT. More... | |

class | edoAlgoAdaptive< D > |

A generic stochastic search template for algorithms that need a distribution parameter. More... | |

class | edoAlgoStateless< D > |

A generic stochastic search template for algorithms that need a distribution parameter but replace it rather than update it. More... | |

## Modules | |

CMAES | |

CMA-ES (Covariance Matrix Adaptation Evolution Strategy) is a stochastic, derivative-free methods for numerical optimization of non-linear or non-convex continuous optimization problems. | |

EMNA | |

Estimation of Multivariate Normal Algorithm (EMNA) is a stochastic, derivative-free methods for numerical optimization of non-linear or non-convex continuous optimization problems. |

In EDO, as in EO, an algorithm is a functor that takes one or several solutions to an optimization problem as arguments, and iteratively modify them with the help of operators.It differs from a canonical EO algorithm because it is templatized on a edoDistrib rather than just an EOT.

**See also:**- eoAlgo