DE_ex.m | Optimization of the Rosenbrock function via differential evolution. |

demand.m | Demand subroutine for the (s,S) inventory problem. |

demandsize.m | Generates the size of the demand for the (s,S) inventory problem. |

f.m | Cost function for the inventory system. Uses demand.m, demandsize.m, interarrival.m, leadtime.m, and order.m. |

GA_ex_fig.m | An application of a binary-encoded genetic algorithm to the satisfiability (SAT) problem. Uses SATdata.mat and sC.c. |

interarrival.m | Generates a demand interarrival time for the (s,S) inventory problem. |

leadtime.m | Generates a lead time for the order in the (s,S) inventory problem. |

opt_policy.m | Noisy optimization for an (s,S) inventory problem, using cross-entropy. Uses f.m. |

order.m | Order subroutine for the (s,S) inventory problem. |

SA.m | An example of continuous optimization using simulated annealing. |

SAnnealing_Multi_SA.m | Comparison of exact and approximate sampling from the Boltzmann distribution in the simulated annealing example. |

SATdata.mat | Contains the SAT instance used in the book. Load into the workspace via "load SATdata.mat". |

sC.c | Evaluates the SAT score function efficiently, given a *sparse* matrix. Must first be compiled within Matlab, using "mex sC.c". |

SCM.m | CE optimization via the stochastic counterpart method. |

SCMb.m | Similar to SCM.m. Estimates for mu and sigma are plotted. |

StochApprox.m | Noisy optimization example using stochastic approximation. |

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