Submitter Variables Constraints Density Status Group Objective MPS File
Gleb Belov 10218 12309 2.60667e-04 easy traininstance 28290 traininstance6.mps.gz

Linearized Constraint Programming models of the MiniZinc Challenges 2012-2016. I should be able to produce versions with indicator constraints supported by Gurobi and CPLEX, however don’t know if you can use them and if there is a standard format. These MPS were produced by Gurobi 7.0.2 using the MiniZinc develop branch on eb536656062ca13325a96b5d0881742c7d0e3c38

Instance Statistics

Detailed explanation of the following tables can be found here.

Size Related Properties
Original Presolved
Variables 10218 10163
Constraints 12309 12256
Binaries 4154 4104
Integers 2056 2051
Continuous 4008 4008
Implicit Integers 0 4
Fixed Variables 11 0
Nonzero Density 0.000260667 0.000261871
Nonzeroes 32785 32618
Constraint Classification Properties
Original Presolved
Total 12309 12256
Empty 0 0
Free 0 0
Singleton 0 0
Aggregations 8051 8046
Precedence 82 65
Variable Bound 25 30
Set Partitioning 14 7
Set Packing 0 0
Set Covering 0 0
Cardinality 9 7
Invariant Knapsack 10 7
Equation Knapsack 0 0
Bin Packing 0 0
Knapsack 2 0
Integer Knapsack 0 0
Mixed Binary 4000 4000
General Linear 116 94
Indicator 0 0

Structure

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

value min median mean max
Components 1.431364
Constraint % 0.0081600 3.78495 0.0244798 24.4798
Variable % 0.0196425 3.81782 0.0392850 24.5728
Score 0.743471

Best Known Solution(s)

Find solutions below. Download the archive containing all solutions from the Download page.

ID Objective Exact Int. Viol Cons. Viol Obj. Viol Submitter Date Description
1 28290 28290 0 0 0 - 2018-10-12 Solution found during MIPLIB2017 problem selection.

Similar instances in collection

The following instances are most similar to traininstance6 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
traininstance2 12890 5278 2602 5010 15603 41531 Gleb Belov traininstance hard 71820
neos-585467 2116 846 0 1270 2166 50058 NEOS Server Submission neos-pseudoapplication-92 open
neos-585192 2597 1044 0 1553 2628 72396 NEOS Server Submission neos-pseudoapplication-92 easy 452.315841359643
neos-4264598-oueme 54550 13370 0 41180 54714 191146 Jeff Linderoth neos-pseudoapplication-57 open 6038453.676499*
radiationm40-10-02 172013 62400 47213 62400 173603 406825 Gleb Belov radiation hard 155328

Reference

@Inbook{Belov2016,
author="Belov, Gleb
and Stuckey, Peter J.
and Tack, Guido
and Wallace, Mark",
editor="Rueher, Michel",
title="Improved Linearization of Constraint Programming Models",
bookTitle="Principles and Practice of Constraint Programming: 22nd International Conference, CP 2016, Toulouse, France, September 5-9, 2016, Proceedings",
year="2016",
publisher="Springer International Publishing",
pages="49--65",
isbn="978-3-319-44953-1",
doi="10.1007/978-3-319-44953-1_4",
url="http://dx.doi.org/10.1007/978-3-319-44953-1_4"
}

Last Update Nov 19, 2018 by Gregor Hendel
generated with R Markdown
© 2018 by Konrad-Zuse-Zentrum für Informationstechnik Berlin (ZIB)
Imprint