Instance - umts


	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	mappingmesh3x3mpeg2i [MIPLIB]	neos-3048764-nadi [MIPLIB]	tr12-30 [MIPLIB]	neos2 [MIPLIB]	ran12x21 [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 / 0.592	2 / 0.641	3 / 0.653	4 / 0.663	5 / 0.673
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	gus-sch [MIPLIB]	comp08-2idx [MIPLIB]	neos-3682128-sandon [MIPLIB]	tw-myciel4 [MIPLIB]	aligninq [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.	28 / 0.743	120 / 0.933	624 / 1.698	659 / 1.751	667 / 1.761
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 umts, the five most similar instances to umts according to the MIC, and the five most similar instances to umts according to MIPLIB 2017.

	INSTANCE	SUBMITTER	DESCRIPTION	ISS	RANK
Parent Instance	umts [MIPLIB]	C. Polo	Telecommunications network model	0.000000	-
MIC Top 5	mappingmesh3x3mpeg2i [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	0.591631	1
	neos-3048764-nadi [MIPLIB]	Jeff Linderoth	(None provided)	0.640848	2
	tr12-30 [MIPLIB]	MIPLIB submission pool	Imported from the MIPLIB2010 submissions.	0.652700	3
	neos2 [MIPLIB]	NEOS Server Submission	Imported from the MIPLIB2010 submissions.	0.662701	4
	ran12x21 [MIPLIB]	J. Aronson	Fixed charge transportation problem	0.672696	5
MIPLIB Top 5	gus-sch [MIPLIB]	Alexandra M. Newman	course scheduling model	0.742919	28
	comp08-2idx [MIPLIB]	Matias Sørensen	Instances comp01-21 of curriculum based course timetabling from the International Timetabling Competition 2007. These are time-assignment models (Stage I of the decomposed model), which are smaller than the full model, but still hard to solve.	0.932581	120
	neos-3682128-sandon [MIPLIB]	Hans Mittelmann	Collection of anonymous submissions to the NEOS Server for Optimization	1.697877	624
	tw-myciel4 [MIPLIB]	Arie Koster	Model to compute the treewidth of the Mycielski-4 instance from the DIMACS graph coloring database. Solved in June 2013 by CPLEX 12.5.1 (12 threads) in about 66 hours. The solving was performed in two steps: first solving with 50 GB tree memory limit (took 11307.42 seconds), after that, setting the tree memory limit to 80 GB and switching to depth first search (took 226152.14 seconds).	1.751252	659
	aligninq [MIPLIB]	MIPLIB submission pool	Imported from the MIPLIB2010 submissions.	1.760962	667

These are model group composite (MGC) images for the MIC top 5 model groups.
Name	mapping	nus-prxy	seqsolve	radiation	graphs
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 / 0.947	2 / 1.064	3 / 1.135	4 / 1.156	5 / 1.169

Model Group Summary

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

	MODEL GROUP	SUBMITTER	DESCRIPTION	ISS	RANK
MIC Top 5	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	0.947460	1
	nus-prxy	MIPLIB submission pool	Imported from the MIPLIB2010 submissions.	1.063838	2
	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.	1.135251	3
	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	1.156359	4
	graphs	Michael Bastubbe	Packing Cuts in Undirected Graphs. Models are described in 4.1.	1.168855	5

Type:	Instance
Submitter:	C. Polo
Description:	Telecommunications network model
	MIPLIB Entry

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

umts: Instance-to-Instance Comparison Results

Parent Instance (umts)

MIC Top 5 Instances

MIPLIB Top 5 Instances

Instance Summary

umts: Instance-to-Model Comparison Results

MIC Top 5 Model Groups

Model Group Summary