Instance - mas74


	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	mas76 [MIPLIB]	pb-market-split8-70-4 [MIPLIB]	gen-ip016 [MIPLIB]	gen-ip002 [MIPLIB]	gen-ip021 [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 / 0.597	2 / 0.692	3 / 0.784	4 / 0.794	5 / 0.806
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	mas76 [MIPLIB]	ns1456591 [MIPLIB]	swath [MIPLIB]	leo2 [MIPLIB]	leo1 [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.	1 / 0.597	371 / 1.541	685 / 1.681	930 / 2.151	932 / 2.155
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 mas74, the five most similar instances to mas74 according to the MIC, and the five most similar instances to mas74 according to MIPLIB 2017.

	INSTANCE	SUBMITTER	DESCRIPTION	ISS	RANK
Parent Instance	mas74 [MIPLIB]	MIPLIB submission pool	Imported from the MIPLIB2010 submissions.	0.000000	-
MIC Top 5	mas76 [MIPLIB]	MIPLIB submission pool	Imported from the MIPLIB2010 submissions.	0.597495	1
	pb-market-split8-70-4 [MIPLIB]	Gleb Belov	These are the instances 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 instances can only be handled by solvers accepting indicator constraints. For instances 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 instances with full paths to mzn/dzn files of each instance 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 instance 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	0.691509	2
	gen-ip016 [MIPLIB]	Simon Bowly	Randomly generated integer and binary programming instances. These results are part of an early phase of work aimed at generating diverse and challenging MIP instances for experimental testing. We have aimed to produce small integer and binary programming instances which are reasonably difficult to solve and have varied structure, eliciting a range of behaviour in state of the art algorithms. Solved with XPRESS in a few seconds.	0.783791	3
	gen-ip002 [MIPLIB]	Simon Bowly	Randomly generated integer and binary programming instances. These results are part of an early phase of work aimed at generating diverse and challenging MIP instances for experimental testing. We have aimed to produce small integer and binary programming instances which are reasonably difficult to solve and have varied structure, eliciting a range of behaviour in state of the art algorithms.	0.794198	4
	gen-ip021 [MIPLIB]	Simon Bowly	Randomly generated integer and binary programming instances. These results are part of an early phase of work aimed at generating diverse and challenging MIP instances for experimental testing. We have aimed to produce small integer and binary programming instances which are reasonably difficult to solve and have varied structure, eliciting a range of behaviour in state of the art algorithms.	0.805637	5
MIPLIB Top 5	mas76 [MIPLIB]	MIPLIB submission pool	Imported from the MIPLIB2010 submissions.	0.597495	1
	ns1456591 [MIPLIB]	NEOS Server Submission	Instance coming from the NEOS Server with unknown application	1.541001	371
	swath [MIPLIB]	D. Panton	Model arising from the defense industry, involves planning missions for radar surveillance. John Forrest and Laszlo Ladanyi solved this instance by reformulation in 1999. Alkis Vazacopoulos reports solving this instance using XPRESS 2006B.	1.680926	685
	leo2 [MIPLIB]	COR@L test set	Instance coming from the COR@L test set with unknown origin	2.151129	930
	leo1 [MIPLIB]	COR@L test set	Instance coming from the COR@L test set with unknown origin	2.154870	932

These are model group composite (MGC) images for the MIC top 5 model groups.
Name	scp	markshare	neos-pseudoapplication-21	stein	enlight
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 / 0.658	2 / 0.719	3 / 0.898	4 / 0.938	5 / 1.186

Model Group Summary

The table below contains summary information for the five most similar model groups to mas74 according to the MIC.

	MODEL GROUP	SUBMITTER	DESCRIPTION	ISS	RANK
MIC Top 5	scp	Shunji Umetani	This is a random test model generator for SCP using the scheme of the following paper, namely the column cost c[j] are integer randomly generated from [1,100]; every column covers at least one row; and every row is covered by at least two columns. see reference: E. Balas and A. Ho, Set covering algorithms using cutting planes, heuristics, and subgradient optimization: A computational study, Mathematical Programming, 12 (1980), 37-60. We have newly generated Classes I-N with the following parameter values, where each class has five models. We have also generated reduced models by a standard pricing method in the following paper: S. Umetani and M. Yagiura, Relaxation heuristics for the set covering problem, Journal of the Operations Research Society of Japan, 50 (2007), 350-375. You can obtain the model generator program from the following web site. https://sites.google.com/site/shunjiumetani/benchmark	0.657634	1
	markshare	G. Cornuéjols, M. Dawande	Market sharing problem	0.719390	2
	neos-pseudoapplication-21	NEOS Server Submission	Imported from the MIPLIB2010 submissions.	0.898367	3
	stein	MIPLIB submission pool	Imported from the MIPLIB2010 submissions.	0.938264	4
	enlight	A. Zymolka	Model to solve model of a combinatorial game ``EnLight'' Imported from the MIPLIB2010 submissions.	1.185751	5

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

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

mas74: Instance-to-Instance Comparison Results

Parent Instance (mas74)

MIC Top 5 Instances

MIPLIB Top 5 Instances

Instance Summary

mas74: Instance-to-Model Comparison Results

MIC Top 5 Model Groups

Model Group Summary