Instance - cbs-cta

cbs-cta: Instance-to-Instance Comparison Results

Type:	Instance
Submitter:	Jordi Castro
Description:	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.
	MIPLIB Entry


	Raw This is the CCM image before the decomposition procedure has been applied.	Decomposed This is the CCM image after a decomposition procedure has been applied. This is the image used by the MIC's image-based comparisons for this query instance.	Composite of MIC Top 5 Composite of the five decomposed CCM images from the MIC Top 5.	Composite of MIPLIB Top 5 Composite of the five decomposed CCM images from the MIPLIB Top 5.	Model Group Composite Image Composite of the decomposed CCM images for every instance in the same model group as this query.

Decomposed These decomposed images were created by GCG.
Name	neos-4290317-perth [MIPLIB]	radiationm40-10-02 [MIPLIB]	neos-824661 [MIPLIB]	neos-876808 [MIPLIB]	radiationm18-12-05 [MIPLIB]
Rank / ISS The image-based structural similarity (ISS) metric measures the Euclidean distance between the image-based feature vectors for the query instance and all other instances. A smaller ISS value indicates greater similarity.	1 / 0.528	2 / 0.538	3 / 0.561	4 / 0.562	5 / 0.567
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIC top 5.

Decomposed These decomposed images were created by GCG.
Name	neos-5075914-elvire [MIPLIB]	neos-4264598-oueme [MIPLIB]	neos-4232544-orira [MIPLIB]	neos-4358725-tagus [MIPLIB]	minutedispatchstrategy [MIPLIB]
Rank / ISS The image-based structural similarity (ISS) metric measures the Euclidean distance between the image-based feature vectors for the query instance and all model groups. A smaller ISS value indicates greater similarity.	377 / 1.310	553 / 1.515	605 / 1.596	651 / 1.687	652 / 1.688
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIPLIB top 5.

Instance Summary

The table below contains summary information for cbs-cta, the five most similar instances to cbs-cta according to the MIC, and the five most similar instances to cbs-cta according to MIPLIB 2017.

	INSTANCE	SUBMITTER	DESCRIPTION	ISS	RANK
Parent Instance	cbs-cta [MIPLIB]	Jordi Castro	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.	0.000000	-
MIC Top 5	neos-4290317-perth [MIPLIB]	Jeff Linderoth	(None provided)	0.527629	1
	radiationm40-10-02 [MIPLIB]	Gleb Belov	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	0.538406	2
	neos-824661 [MIPLIB]	NEOS Server Submission	Instance coming from the NEOS Server with unknown application	0.561407	3
	neos-876808 [MIPLIB]	NEOS Server Submission	Imported from the MIPLIB2010 submissions.	0.561809	4
	radiationm18-12-05 [MIPLIB]	Gleb Belov	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	0.566581	5
MIPLIB Top 5	neos-5075914-elvire [MIPLIB]	Jeff Linderoth	(None provided)	1.309790	377
	neos-4264598-oueme [MIPLIB]	Jeff Linderoth	(None provided)	1.514821	553
	neos-4232544-orira [MIPLIB]	Jeff Linderoth	(None provided)	1.596048	605
	neos-4358725-tagus [MIPLIB]	Jeff Linderoth	(None provided)	1.687453	651
	minutedispatchstrategy [MIPLIB]	Mark Husted	Dispatch Strategy for a small micro-grid	1.687605	652

cbs-cta: Instance-to-Model Comparison Results

Model Group Assignment from MIPLIB:	cta
Assigned Model Group Rank/ISS in the MIC:	164 / 3.224

These are model group composite (MGC) images for the MIC top 5 model groups.
Name	seqsolve	radiation	n37	mapping	sp_product
Rank / ISS The image-based structural similarity (ISS) metric measures the Euclidean distance between the image-based feature vectors for the query instance and all other instances. A smaller ISS value indicates greater similarity.	1 / 0.939	2 / 1.138	3 / 1.146	4 / 1.161	5 / 1.169

Model Group Summary

The table below contains summary information for the five most similar model groups to cbs-cta according to the MIC.

	MODEL GROUP	SUBMITTER	DESCRIPTION	ISS	RANK
MIC Top 5	seqsolve	Irv Lustig	The 3 problems in this group (seqsolve1-seqsolve3) represent a hierarchical optimization process, which is derived from a customer problem for assigning people to sites into blocks of time on days of the week. The specialty of this submission is that the best known solution for seqsolveX can be used as a MIP start for seqsolveX+1. For a description of the connections between the problems, please refer to the README.txt contained in the model data for this submission, which also includes MIP start files and a Gurobi log file.	0.939041	1
	radiation	Gleb Belov	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	1.137835	2
	n37	J. Aronson	Fixed charge transportation problem	1.145870	3
	mapping	Gleb Belov	These are the models from MiniZinc Challenges 2012-2016 (see www.minizinc.org), compiled for MIP WITH INDICATOR CONSTRAINTS using the develop branch of MiniZinc and CPLEX 12.7.1 on 30 April 2017. Thus, these models can only be handled by solvers accepting indicator constraints. For models compiled with big-M/domain decomposition only, see my previous submission to MIPLIB.To recompile, create a directory MODELS, a list lst12_16.txt of the models with full paths to mzn/dzn files of each model per line, and say$> ~/install/libmzn/tests/benchmarking/mzn-test.py -l ../lst12_16.txt -slvPrf MZN-CPLEX -debug 1 -addOption "-timeout 3 -D fIndConstr=true -D fMIPdomains=false" -useJoinedName "-writeModel MODELS_IND/%s.mps" Alternatively, you can compile individual model as follows: $> mzn-cplex -v -s -G linear -output-time ../challenge_2012_2016/mznc2016_probs/zephyrus/zephyrus.mzn ../challenge_2012_2016/mznc2016_p/zephyrus/14__8__6__3.dzn -a -timeout 3 -D fIndConstr=true -D fMIPdomains=false -writeModel MODELS_IND/challenge_2012_2016mznc2016_probszephyruszephyrusmzn-challenge_2012_2016mznc2016_probszephyrus14__8__6__3dzn.mps	1.160540	4
	sp_product	MIPLIB submission pool	Imported from the MIPLIB2010 submissions.	1.169460	5

cbs-cta: Instance-to-Instance Comparison Results

Parent Instance (cbs-cta)

MIC Top 5 Instances

MIPLIB Top 5 Instances

Instance Summary

cbs-cta: Instance-to-Model Comparison Results

MIC Top 5 Model Groups

Model Group Summary