Instance - ta1-UUM


	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	fastxgemm-n2r6s0t2 [MIPLIB]	fastxgemm-n2r7s4t1 [MIPLIB]	sct5 [MIPLIB]	mitre [MIPLIB]	neos-3615091-sutlej [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 / 0.757	2 / 0.759	3 / 0.805	4 / 0.865	5 / 0.869
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	n9-3 [MIPLIB]	n5-3 [MIPLIB]	neos-3421095-cinca [MIPLIB]	ger50-17-ptp-pop-6t [MIPLIB]	ger50-17-ptp-pop-3t* [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.	95 / 1.186	228 / 1.337	462 / 1.541	531 / 1.621	531* / 1.621*
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 ta1-UUM, the five most similar instances to ta1-UUM according to the MIC, and the five most similar instances to ta1-UUM according to MIPLIB 2017.

	INSTANCE	SUBMITTER	DESCRIPTION	ISS	RANK
Parent Instance	ta1-UUM [MIPLIB]	MIPLIB submission pool	Imported from the MIPLIB2010 submissions.	0.000000	-
MIC Top 5	fastxgemm-n2r6s0t2 [MIPLIB]	Laurent Sorber	Naive multiplication of two N by N matrices requires N^3 scalar multiplications. For N=2, Strassen showed that it could be done in only R=7 < 8=N^3 multiplications. For N=3, it is known that 19 <= R <= 23, and for N=4 it is known that 34 <= R <= 49. This repository contains code that generates a mixed-integer linear program (MILP) formulation of the fast matrix multiplication problem for finding solutions with R < N^3 and proving that they are optimal. For a more detailed description, see the accompanying manuscript.	0.756554	1
	fastxgemm-n2r7s4t1 [MIPLIB]	Laurent Sorber	Naive multiplication of two N by N matrices requires N^3 scalar multiplications. For N=2, Strassen showed that it could be done in only R=7 < 8=N^3 multiplications. For N=3, it is known that 19 <= R <= 23, and for N=4 it is known that 34 <= R <= 49. This repository contains code that generates a mixed-integer linear program (MILP) formulation of the fast matrix multiplication problem for finding solutions with R < N^3 and proving that they are optimal. For a more detailed description, see the accompanying manuscript.	0.759254	2
	sct5 [MIPLIB]	Siemens	Assembly line balancing for printed circuit board production	0.804993	3
	mitre [MIPLIB]	MIPLIB submission pool	Imported from the MIPLIB2010 submissions.	0.864982	4
	neos-3615091-sutlej [MIPLIB]	Hans Mittelmann	Collection of anonymous submissions to the NEOS Server for Optimization	0.869456	5
MIPLIB Top 5	n9-3 [MIPLIB]	A. Atamtürk	Capacitated network design problem	1.185876	95
	n5-3 [MIPLIB]	A. Atamtürk	Capacitated network design problem	1.337415	228
	neos-3421095-cinca [MIPLIB]	Jeff Linderoth	(None provided)	1.540787	462
	ger50-17-ptp-pop-6t [MIPLIB]	C. Raack	Multi-layer network design problem using a link-flow formulation over a path-flow formulation.	1.621165	531
	ger50-17-ptp-pop-3t* [MIPLIB]	C. Raack	Multi-layer network design problem using a link-flow formulation over a path-flow formulation.	1.621165*	531*

These are model group composite (MGC) images for the MIC top 5 model groups.
Name	supportvectormachine	hypothyroid	mapping	noip	square
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 / 1.529	2 / 1.570	3 / 1.616	4 / 1.634	5 / 1.655

Model Group Summary

The table below contains summary information for the five most similar model groups to ta1-UUM according to the MIC.

	MODEL GROUP	SUBMITTER	DESCRIPTION	ISS	RANK
MIC Top 5	supportvectormachine	Toni Sorrell	Suport vector machine with ramp loss. GSVM2-RL is the formulation found in Hess E. and Brooks P. (2015) paper, The Support Vector Machine and Mixed Integer Linear Programming: Ramp Loss SVM with L1-Norm Regularization	1.528598	1
	hypothyroid	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	1.570427	2
	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	1.615778	3
	noip	Christopher Hojny	integer programming formulation that verifies that no integer programming formulation of a given 0/1-point set exists	1.634173	4
	square	Sascha Kurz	Squaring the square For a given integer n, determine the minimum number of squares in a tiling of an \$n\\times n\$ square using using only integer sided squares of smaller size. (Although the models get quite large even for moderate n, they can be solved to optimality for all \$n \\le 61\$, while challenging the MIP solver, especially the presolver.)	1.655497	5

Type:	Instance
Submitter:	MIPLIB submission pool
Description:	Imported from the MIPLIB2010 submissions.
	MIPLIB Entry

Model Group Assignment from MIPLIB:	network_design
Assigned Model Group Rank/ISS in the MIC:	162 / 3.042

ta1-UUM: Instance-to-Instance Comparison Results

Parent Instance (ta1-UUM)

MIC Top 5 Instances

MIPLIB Top 5 Instances

Instance Summary

ta1-UUM: Instance-to-Model Comparison Results

MIC Top 5 Model Groups

Model Group Summary