Submitter Variables Constraints Density Status Group Objective MPS File
Jordi Castro 37951 20097 1.38245e-04 easy cta 0 dale-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 37951 34785
Constraints 20097 20097
Binaries 4923 4923
Integers 0 0
Continuous 33028 29862
Implicit Integers 0 0
Fixed Variables 3166 0
Nonzero Density 0.000138245 0.000141770
Nonzeroes 105440 99108
Constraint Classification Properties
Original Presolved
Total 20097 20097
Empty 0 0
Free 0 0
Singleton 0 0
Aggregations 0 0
Precedence 0 0
Variable Bound 19692 19692
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 405 405
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 3.692318
Constraint % 0.0199035 0.0199035 0.0199035 0.0199035
Variable % 0.0086200 0.0086200 0.0086200 0.0086200
Score 0.979763

Best Known Solution(s)

No solution available for dale-cta .

Similar instances in collection

The following instances are most similar to dale-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
tr12-30 1080 360 0 720 750 2508 MIPLIB submission pool easy 130596.0
bg512142 792 240 0 552 1307 3953 A. Miller hard 184202.8
dg012142 2080 640 0 1440 6310 14795 A. Miller hard 2300867.0
mc11 3040 1520 0 1520 1920 6080 F. Ortega, L. Wolsey mc easy 11689.0
mc8 3040 1520 0 1520 1920 6080 F. Ortega, L. Wolsey mc easy 1566.0

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 17, 2018 by Gregor Hendel
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