# 16 List of examples¶

List of examples shipped in the distribution of Fusion API for Matlab:

File | Description |
---|---|

`MatlabCallback.java` |
A Java class implementing data callback for `callback.m` |

`TrafficNetworkModel.m` |
Demonstrates a traffic network problem as a conic quadratic problem (CQO) |

`alan.m` |
A portfolio choice model `alan.gms` from the GAMS model library |

`baker.m` |
A small bakery revenue maximization linear problem |

`callback.m` |
An example of data/progress callback |

`cqo1.m` |
A simple conic quadratic problem |

`diet.m` |
Solving Stigler’s Nutrition model `diet` from the GAMS model library |

`duality.m` |
Shows how to access the dual solution |

`facility_location.m` |
Demonstrates a small one-facility location problem (CQO) |

`lo1.m` |
A simple linear problem |

`lownerjohn_ellipsoid.m` |
Computes the Lowner-John inner and outer ellipsoidal approximations of a polytope (SDO, CQO) |

`lpt.m` |
Demonstrates how to solve the multi-processor scheduling problem and input an integer feasible point (MIP) |

`milo1.m` |
A simple mixed-integer linear problem |

`mioinitsol.m` |
A simple mixed-integer linear problem with an initial guess |

`model_utils.m` |
Models for the geometric mean and determinant |

`nearestcorr.m` |
Solves the nearest correlation matrix problem (SDO, CQO) |

`parameters.m` |
Shows how to set optimizer parameters and read information items |

`portfolio.m` |
Presents several portfolio optimization models |

`primal_svm.m` |
Implements a simple soft-margin Support Vector Machine (CQO) |

`production.m` |
Demonstrate how to modify and re-optimize a linear problem |

`qcqp_sdo_relaxation.m` |
Demonstrate how to use SDP to solve convex relaxation of a mixed-integer QCQO problem |

`sdo1.m` |
A simple semidefinite optimization problem |

`sospoly.m` |
Models the cone of nonnegative polynomials and nonnegative trigonometric polynomials using Nesterov’s framework |

`sudoku.m` |
A SUDOKU solver (MIP) |

`total_variation.m` |
Demonstrates how to solve a total variation problem (CQO) |

`tsp.m` |
Solves a simple Travelling Salesman Problem and shows how to add constraints to a model and re-optimize (MIP) |

Additional examples can be found on the **MOSEK** website and in other **MOSEK** publications.