Instance - snip10x10-35r1budget17

snip10x10-35r1budget17: Instance-to-Instance Comparison Results

Type:	Instance
Submitter:	Utz-Uwe Haus
Description:	Exact MILP reformulation using binary decision diagrams to obtain scenario bundles of 2-stage stochastic expected shortest path and expected maximum flow problem with decision dependent scenario probabilities. Notes: * very few binary variables * for each fixing of the binaries a system of equations computing conditioned probabilities remains
	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-829552 [MIPLIB]	neos-633273 [MIPLIB]	neos-831188 [MIPLIB]	fhnw-schedule-pairb400 [MIPLIB]	fhnw-schedule-pairb200 [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 / 0.766	2 / 0.788	3 / 0.795	4 / 0.845	5 / 0.896
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	istanbul-no-cutoff [MIPLIB]	nsa [MIPLIB]	net12 [MIPLIB]	neos-5188808-nattai [MIPLIB]	neos-691058 [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.	380 / 1.653	507 / 1.732	587 / 1.792	766 / 2.032	826 / 2.191
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 snip10x10-35r1budget17, the five most similar instances to snip10x10-35r1budget17 according to the MIC, and the five most similar instances to snip10x10-35r1budget17 according to MIPLIB 2017.

	INSTANCE	SUBMITTER	DESCRIPTION	ISS	RANK
Parent Instance	snip10x10-35r1budget17 [MIPLIB]	Utz-Uwe Haus	Exact MILP reformulation using binary decision diagrams to obtain scenario bundles of 2-stage stochastic expected shortest path and expected maximum flow problem with decision dependent scenario probabilities. Notes: * very few binary variables * for each fixing of the binaries a system of equations computing conditioned probabilities remains	0.000000	-
MIC Top 5	neos-829552 [MIPLIB]	NEOS Server Submission	Imported from the MIPLIB2010 submissions.	0.766344	1
	neos-633273 [MIPLIB]	NEOS Server Submission	Collection of anonymous submissions to the NEOS Server for Optimization	0.787921	2
	neos-831188 [MIPLIB]	NEOS Server Submission	Imported from the MIPLIB2010 submissions.	0.795383	3
	fhnw-schedule-pairb400 [MIPLIB]	Simon Felix	Continuous-time project scheduling and selection, inspired by an industry use-case. Each project has a value, the sum should be maximized. Each project has a deadline, and an earliest start date. Three formulations of the same problem ("Pair A", "Pair B" and "Slot") - we expect "Pair B" to be the best formulation.	0.844706	4
	fhnw-schedule-pairb200 [MIPLIB]	Simon Felix	Continuous-time project scheduling and selection, inspired by an industry use-case. Each project has a value, the sum should be maximized. Each project has a deadline, and an earliest start date. Three formulations of the same problem ("Pair A", "Pair B" and "Slot") - we expect "Pair B" to be the best formulation.	0.895589	5
MIPLIB Top 5	istanbul-no-cutoff [MIPLIB]	Utz-Uwe Haus	Exact MILP reformulation using binary decision diagrams to obtain scenario bundles of 2-stage stochastic expected shortest path and expected maximum flow problem with decision dependent scenario probabilities. Notes: * very few binary variables * for each fixing of the binaries a system of equations computing conditioned probabilities remains	1.653447	380
	nsa [MIPLIB]	MIPLIB submission pool	Imported from the MIPLIB2010 submissions.	1.731964	507
	net12 [MIPLIB]	P. Belotti	Network design instance	1.792476	587
	neos-5188808-nattai [MIPLIB]	Jeff Linderoth	(None provided)	2.032054	766
	neos-691058 [MIPLIB]	NEOS Server Submission	Imported from the MIPLIB2010 submissions.	2.191373	826

snip10x10-35r1budget17: Instance-to-Model Comparison Results

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

These are model group composite (MGC) images for the MIC top 5 model groups.
Name	8div	neos-pseudoapplication-95	proteindesign	rpp	neos-pseudoapplication-74
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 / 1.468	2 / 1.569	3 / 1.760	4 / 1.847	5 / 1.859

Model Group Summary

The table below contains summary information for the five most similar model groups to snip10x10-35r1budget17 according to the MIC.

	MODEL GROUP	SUBMITTER	DESCRIPTION	ISS	RANK
MIC Top 5	8div	Sascha Kurz	Projective binary 8-divisible linear block codes A linear block code is called 8-divisible if the weights of its codewords are divisible by 8. It is called projective if there are no duplicate columns in the generator matrix. The possible lengths of 8-divisible linear block codes have been classified except for length n=59, where it is undecided whether such a linear code exists. The possible dimensions satisfy \$10 \\le k \\le 20\$. Model 8div_n59_kXX contains the corresponding feasibility problem. Projective binary 8-divisible linear block codes occur as hole configurations of so-called partial solid spreads in finite geometry. Binary 4-divisible linear block codes have applications in physics.	1.467622	1
	neos-pseudoapplication-95	NEOS Server Submission	Imported from the MIPLIB2010 submissions.	1.568941	2
	proteindesign	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	1.759689	3
	rpp	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	1.846764	4
	neos-pseudoapplication-74	Jeff Linderoth	(None provided)	1.859481	5

snip10x10-35r1budget17: Instance-to-Instance Comparison Results

Parent Instance (snip10x10-35r1budget17)

MIC Top 5 Instances

MIPLIB Top 5 Instances

Instance Summary

snip10x10-35r1budget17: Instance-to-Model Comparison Results

MIC Top 5 Model Groups

Model Group Summary