Submitter | Variables | Constraints | Density | Status | Group | Objective | MPS File |
---|---|---|---|---|---|---|---|

Dimitri Papageorgiou | 92261 | 126621 | 5.37544e-05 | easy | maritime | Infeasible | maritime-jg3d9.mps.gz |

Maritime Inventory Routing Problems: Jiang-Grossmann Instances. These instances are available at https://mirplib.scl.gatech.edu/instances, along with a host of additional information such as the underlying data used to generate the model, best known upper and lower bounds, and more. They involve a single product maritime inventory routing problem and explore the use of continuous and discrete time models. A continuous-time model based on time slots for single docks is used for some instances. A model based on event points to handle parallel docks is used in others. A discrete time model based on a single commodity fixed-charge network flow problem (FCNF) is used for other instances. All the models are solved for multiple randomly generated instances of different problems to compare their computational efficiency.

Detailed explanation of the following tables can be found here.

Original | Presolved | |
---|---|---|

Variables | 92261 | 33368 |

Constraints | 126621 | 35785 |

Binaries | 36960 | 5525 |

Integers | 0 | 1 |

Continuous | 55301 | 27842 |

Implicit Integers | 0 | 1 |

Fixed Variables | 11 | 0 |

Nonzero Density | 5.37544e-05 | 1.43146e-04 |

Nonzeroes | 627969 | 170927 |

Original | Presolved | |
---|---|---|

Total | 126621 | 35785 |

Empty | 0 | 0 |

Free | 0 | 0 |

Singleton | 29564 | 0 |

Aggregations | 0 | 24141 |

Precedence | 0 | 1367 |

Variable Bound | 53784 | 3011 |

Set Partitioning | 15 | 24 |

Set Packing | 4152 | 1573 |

Set Covering | 0 | 0 |

Cardinality | 5055 | 1909 |

Invariant Knapsack | 3384 | 1388 |

Equation Knapsack | 0 | 0 |

Bin Packing | 0 | 0 |

Knapsack | 0 | 0 |

Integer Knapsack | 0 | 0 |

Mixed Binary | 30667 | 2371 |

General Linear | 0 | 1 |

Indicator | 0 | 0 |

Available nonzero structure and decomposition information. Further information can be found here.

Decomposed structure of original problem (dec-file)

Decomposed structure after trivial presolving (dec-file)

value | min | median | mean | max | |
---|---|---|---|---|---|

Components | 2.605305 | ||||

Constraint % | 0.002900 | 0.231677 | 0.173742 | 22.6009 | |

Variable % | 0.181634 | 0.242594 | 0.181634 | 22.5673 | |

Score | 0.879016 |

No solution available for maritime-jg3d9 .

The following instances are most similar to maritime-jg3d9 in the collection. This similarity analysis is based on 100 scaled instance features describing properties of the variables, objective function, bounds, constraints, and right hand sides.

Instance | Variables | Binaries | Integers | Continuous | Constraints | Nonz. | Submitter | Group | Status | Objective |
---|---|---|---|---|---|---|---|---|---|---|

neos-5093327-huahum | 40640 | 64 | 0 | 40576 | 51840 | 784768 | Jeff Linderoth | neos-pseudoapplication-17 | hard | 6260 |

neos-5076235-embley | 49686 | 98 | 0 | 49588 | 63112 | 1089560 | Jeff Linderoth | neos-pseudoapplication-17 | hard | 2362 |

neos-5079731-flyers | 49686 | 98 | 0 | 49588 | 63112 | 1089560 | Jeff Linderoth | neos-pseudoapplication-17 | easy | 2440 |

neos-5100895-inster | 29400 | 56 | 0 | 29344 | 39760 | 693168 | Jeff Linderoth | neos-pseudoapplication-17 | easy | 3132 |

neos-5041822-cockle | 227668 | 149313 | 0 | 78355 | 546733 | 1362470 | Jeff Linderoth | neos-pseudoapplication-25 | open | 5728105.52906* |

```
@article{jiang2015alternative,
title={Alternative mixed-integer linear programming models of a maritime inventory routing problem},
author={Jiang, Yongheng and Grossmann, Ignacio E},
journal={Computers \& Chemical Engineering},
volume={77},
pages={147--161},
year={2015},
publisher={Elsevier}
}
@article{papageorgiou2014mirplib,
title={MIRPLib--A library of maritime inventory routing problem instances: Survey, core model, and benchmark results},
author={Papageorgiou, Dimitri J and Nemhauser, George L and Sokol, Joel and Cheon, Myun-Seok and Keha, Ahmet B},
journal={European Journal of Operational Research},
volume={235},
number={2},
pages={350--366},
year={2014},
publisher={Elsevier}
}
```

Last Update Jan 18, 2019 by Gregor Hendel

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