Submitter Variables Constraints Density Status Group Objective MPS File
Gleb Belov 12890 15603 2.06496e-04 hard traininstance 71820 traininstance2.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 12890 12853
Constraints 15603 15586
Binaries 5278 5247
Integers 2602 2596
Continuous 5010 5010
Implicit Integers 0 5
Fixed Variables 12 0
Nonzero Density 0.000206496 0.000206947
Nonzeroes 41531 41457
Constraint Classification Properties
Original Presolved
Total 15603 15586
Empty 0 0
Free 0 0
Singleton 0 0
Aggregations 10090 10100
Precedence 166 157
Variable Bound 35 44
Set Partitioning 22 10
Set Packing 0 0
Set Covering 0 0
Cardinality 17 16
Invariant Knapsack 17 16
Equation Knapsack 0 0
Bin Packing 0 0
Knapsack 2 0
Integer Knapsack 0 0
Mixed Binary 5000 5000
General Linear 254 243
Indicator 0 0

Structure

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

value min median mean max
Components 1.633468
Constraint % 0.0064200 2.31313 0.0224561 19.2673
Variable % 0.0155473 2.35763 0.0466418 19.4729
Score 0.783913

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 71820 71820 0 0 0 - 2018-10-12 Solution found during MIPLIB2017 problem selection.

Similar instances in collection

The following instances are most similar to traininstance2 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
traininstance6 10218 4154 2056 4008 12309 32785 Gleb Belov traininstance easy 28290
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 09, 2018 by Gregor Hendel
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