Instance - datt256


	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	bppc4-08 [MIPLIB]	core4872-1529 [MIPLIB]	v150d30-2hopcds [MIPLIB]	core4284-1064 [MIPLIB]	air05 [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 / 1.523	2 / 1.673	3 / 1.694	4 / 1.748	5 / 1.776
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	supportcase6 [MIPLIB]	s100 [MIPLIB]	tbfp-network [MIPLIB]	neos-4531126-vouga [MIPLIB]	neos-826224 [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.	24 / 1.907	310 / 2.990	565 / 3.278	765 / 3.426	868 / 3.504
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 datt256, the five most similar instances to datt256 according to the MIC, and the five most similar instances to datt256 according to MIPLIB 2017.

	INSTANCE	SUBMITTER	DESCRIPTION	ISS	RANK
Parent Instance	datt256 [MIPLIB]	Jon Dattorro	Model to find solution to the ``Eternity II'' puzzle	0.000000	-
MIC Top 5	bppc4-08 [MIPLIB]	Manuel Iori	The models that we attach solve the "bar-relaxation", also known as the "Bin Packing Problem with Contiguity" or the "P\|\|Cmax with contiguity". This is one of the most interesting relaxations for two dimensional cutting and packing problems. Its solution by means of an ILP software is the bottleneck of the primal decomposition methods that we attempted in the paper cited below. In detail, the files correspond to model (12)-(15) in the paper, applied to the instances of the Classes 4, 6 and 8 by Martello and Vigo (Management Science, 1998).	1.523284	1
	core4872-1529 [MIPLIB]	A. Caprara, M. Fischetti, P. Toth	Set covering instance coming from Italian railway models	1.672540	2
	v150d30-2hopcds [MIPLIB]	Austin Buchanan	A problem in wireless networks. The objective is to select a minimum number of relay nodes so that any two nonadjacent nodes can communicate by way of the chosen relay nodes in at most s hops, where s is a problem input. The 2-hop case of this problem can be formulated as a set cover/hitting set problem with n binary variables and n^2 constraints: _{ k N(i) N(j) } x_k 1 for nonadjacent node pairs {i,j}. Despite the formulation's simplicity, instances with as few as 120 variables are left unsolved after one hour using Gurobi 7.0.2.	1.693907	3
	core4284-1064 [MIPLIB]	A. Caprara, M. Fischetti, P. Toth	Set covering instance coming from Italian railway models	1.747793	4
	air05 [MIPLIB]	G. Astfalk	Airline crew scheduling set partitioning problem	1.775567	5
MIPLIB Top 5	supportcase6 [MIPLIB]	Michael Winkler	MIP instances collected from Gurobi forum with unknown application	1.906906	24
	s100 [MIPLIB]	Daniel Espinoza	Wine Scheduling problem with 100 jobs and four processing machines	2.989864	310
	tbfp-network [MIPLIB]	Rob Pratt	Two formulations (big-M and network-based) for traveling baseball fan problem. Uses data from 2014 Major League Baseball regular season. Paper uses 2014 data: http://support.sas.com/resources/papers/proceedings14/SAS101-2014.pdf Blog post uses 2015 data: http://blogs.sas.com/content/operations/2015/04/03/the-traveling-baseball-fan-problem/	3.277904	565
	neos-4531126-vouga [MIPLIB]	Jeff Linderoth	(None provided)	3.425690	765
	neos-826224 [MIPLIB]	NEOS Server Submission	Imported from the MIPLIB2010 submissions.	3.504347	868

These are model group composite (MGC) images for the MIC top 5 model groups.
Name	f2gap	pb-	assign1	2hopcds	neos-pseudoapplication-78
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 / 1.639	2 / 1.775	3 / 1.802	4 / 1.818	5 / 1.839

Model Group Summary

The table below contains summary information for the five most similar model groups to datt256 according to the MIC.

	MODEL GROUP	SUBMITTER	DESCRIPTION	ISS	RANK
MIC Top 5	f2gap	Salim Haddadi	Restrictions of well-known hard generalized assignment problem models (D10400,D20400,D40400,D15900,D30900,D60900,D201600,D401600,D801600)	1.638771	1
	pb-	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	1.774874	2
	assign1	Robert Fourer	Imported from the MIPLIB2010 submissions.	1.801929	3
	2hopcds	Austin Buchanan	A problem in wireless networks. The objective is to select a minimum number of relay nodes so that any two nonadjacent nodes can communicate by way of the chosen relay nodes in at most s hops, where s is a problem input. The 2-hop case of this problem can be formulated as a set cover/hitting set problem with n binary variables and n^2 constraints: _{ k N(i) N(j) } x_k 1 for nonadjacent node pairs {i,j}. Despite the formulation's simplicity, models with as few as 120 variables are left unsolved after one hour using Gurobi 7.0.2.	1.817562	4
	neos-pseudoapplication-78	Jeff Linderoth	(None provided)	1.838865	5

Type:	Instance
Submitter:	Jon Dattorro
Description:	Model to find solution to the ``Eternity II'' puzzle
	MIPLIB Entry

Model Group Assignment from MIPLIB:	no model group assignment
Assigned Model Group Rank/ISS in the MIC:	N.A. / N.A.

datt256: Instance-to-Instance Comparison Results

Parent Instance (datt256)

MIC Top 5 Instances

MIPLIB Top 5 Instances

Instance Summary

datt256: Instance-to-Model Comparison Results

MIC Top 5 Model Groups

Model Group Summary