Submitter Variables Constraints Density Status Group Objective MPS File
Jordi Castro 49758 3946 1.72105e-04 open cta 106.0589096029 australia-abs-cta.mps.gz

Set of MILP instances of the CTA (Controlled Tabular Adjustment) problem, a method to protect statistical tabular data, belonging to the field of SDC (Statistical Disclosure Control). Raw data of instances are real or pseudo-real, provided by several National Statistical Agencies. We generated the CTA problem for these data.

Instance Statistics

Detailed explanation of the following tables can be found here.

Size Related Properties
Original Presolved
Variables 49758 14142
Constraints 3946 3946
Binaries 918 918
Integers 0 0
Continuous 48840 13224
Implicit Integers 0 0
Fixed Variables 35616 0
Nonzero Density 0.000172105 0.000605544
Nonzeroes 33792 33792
Constraint Classification Properties
Original Presolved
Total 3946 3946
Empty 0 0
Free 0 0
Singleton 0 0
Aggregations 1 1
Precedence 0 0
Variable Bound 3672 3672
Set Partitioning 0 0
Set Packing 0 0
Set Covering 0 0
Cardinality 0 0
Invariant Knapsack 0 0
Equation Knapsack 0 0
Bin Packing 0 0
Knapsack 0 0
Integer Knapsack 0 0
Mixed Binary 273 273
General Linear 0 0
Indicator 0 0

Structure

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

value min median mean max
Components 2.963788
Constraint % 0.0253421 0.1012860 0.1013680 0.1013680
Variable % 0.0141423 0.0212057 0.0212134 0.0212134
Score 0.930619

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
1 106.0589 106.9047 8e-06 9e-07 0 - 2018-10-11 Solution found during MIPLIB2017 problem selection.

Similar instances in collection

The following instances are most similar to australia-abs-cta 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
cbs-cta 24793 2467 0 22326 10112 64388 Jordi Castro cta easy 0
atm20-100 6480 2220 0 4260 4380 58878 Matthew Galati hard 2463621.57727541
dsbmip 1886 192 0 1694 1182 7366 MIPLIB submission pool easy -305.19817501
misc04inf 4897 30 0 4867 1726 17253 MIPLIB submission pool misc easy Infeasible
dcmulti 548 75 0 473 290 1315 MIPLIB submission pool easy 188182

Reference

@ARTICLE{Castro2006,
  author =       {J. Castro},
  title =        {Minimum-distance controlled perturbation methods for large-scale tabular data protection},
  journal =      {European Journal of Operational Research},
  year =         {2006},
  volume =       {171},
  pages =        {39--52},
}
@ARTICLE{Castro2011,
  author =       {J. A. González, J. Castro},
  title =        {A heuristic block coordinate descent approach for controlled tabular adjustment},
  journal =      {Computers & Operations Research},
  year =         {2011},
  volume =       {38},
  pages =        {1826--1835},
}
@ARTICLE{Castro2012,
  author =       {J. Castro},
  title =        {Recent advances in optimization techniques for statistical tabular data protection},
  journal =      {European Journal of Operational Research},
  year =         {2012},
  volume =       {216},
  pages =        {257--269},
}

@ARTICLE{CastroFrangioniGentile2014,
  author =       {J. Castro, A. Frangioni, C. Gentile},
  title =        {Perspective reformulations of the CTA problem with L2 distances},
  journal =      {Operations Research},
  year =         {2014},
  volume =       {62},
  pages =        {891--909},
}

@ARTICLE{BaenaCastroGonzalez2015,
  author =       {D. Baena, J. Castro, J. A. González},
  title =        {Fix-and-relax approaches for controlled tabular adjustment},
  journal =      {Computers & Operations Research},
  year =         {2015},
  volume =       {58},
  pages =        {41--52},
}

Last Update Nov 09, 2018 by Gregor Hendel
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