Instance - ex9

ex9: Instance-to-Instance Comparison Results

Type:	Instance
Submitter:	Iulian Ober
Description:	Formulations of Boolean SAT instance
	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	ex10 [MIPLIB]	sorrell7 [MIPLIB]	sorrell3 [MIPLIB]	t1722 [MIPLIB]	t1717 [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 / 0.769	2 / 0.869	3 / 0.922	4 / 0.975	5 / 0.997
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	ex10 [MIPLIB]	supportcase10 [MIPLIB]	tw-myciel4 [MIPLIB]	supportcase22 [MIPLIB]	graph20-80-1rand [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 / 0.769	106 / 2.721	177 / 3.162	339 / 3.600	907 / 4.164
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 ex9, the five most similar instances to ex9 according to the MIC, and the five most similar instances to ex9 according to MIPLIB 2017.

	INSTANCE	SUBMITTER	DESCRIPTION	ISS	RANK
Parent Instance	ex9 [MIPLIB]	Iulian Ober	Formulations of Boolean SAT instance	0.000000	-
MIC Top 5	ex10 [MIPLIB]	Iulian Ober	Formulations of Boolean SAT instance	0.769366	1
	sorrell7 [MIPLIB]	Toni Sorrell	These instances are based on Neil Sloane's Challenge problems: Independent Sets in Graphs.	0.868886	2
	sorrell3 [MIPLIB]	Toni Sorrell	These instances are based on Neil Sloane's Challenge problems: Independent Sets in Graphs.	0.922196	3
	t1722 [MIPLIB]	R. Borndörfer	Vehicle scheduling set partitioning problem from Berlin's Telebus handicapped people's transportation system	0.974786	4
	t1717 [MIPLIB]	R. Borndörfer	Vehicle scheduling set partitioning problem from Berlin's Telebus handicapped people's transportation system	0.997027	5
MIPLIB Top 5	ex10 [MIPLIB]	Iulian Ober	Formulations of Boolean SAT instance	0.769366	1
	supportcase10 [MIPLIB]	Michael Winkler	MIP instances collected from Gurobi forum with unknown application	2.721490	106
	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).	3.162432	177
	supportcase22 [MIPLIB]	Michael Winkler	MIP instances collected from Gurobi forum with unknown application	3.599668	339
	graph20-80-1rand [MIPLIB]	Michael Bastubbe	Packing Cuts in Undirected Graphs. Instances are described in 4.1.	4.163858	907

ex9: 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	core	ivu	reblock	air	maritime
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 / 1.143	2 / 1.214	3 / 1.221	4 / 1.353	5 / 1.386

Model Group Summary

The table below contains summary information for the five most similar model groups to ex9 according to the MIC.

	MODEL GROUP	SUBMITTER	DESCRIPTION	ISS	RANK
MIC Top 5	core	A. Caprara, M. Fischetti, P. Toth	Set covering model coming from Italian railway models	1.142620	1
	ivu	S. Weider	Set partitioning model resulting from a column generation algorithm used for duty scheduling in public transportation. Solved in June 2014 using CPLEX 12.6 with 48 threads in about 25 days.	1.214368	2
	reblock	Andreas Bley	Multi-period mine production scheduling model. Solved using ug[SCIP/spx], a distributed massively parallel version of SCIP run on 2,000 cores at the HLRN-II super computer facility.	1.221119	3
	air	G. Astfalk	Airline crew scheduling set partitioning problem	1.352602	4
	maritime	Dimitri Papageorgiou	Maritime Inventory Routing Problems: Jiang-Grossmann Models. These models are available at https://mirplib.scl.gatech.edu/models, along with a host of additional information such as the underlying data used to generate the model, best known upper and lower bounds, and more. They involve a single product maritime inventory routing problem and explore the use of continuous and discrete time models. A continuous-time model based on time slots for single docks is used for some models. A model based on event points to handle parallel docks is used in others. A discrete time model based on a single commodity fixed-charge network flow problem (FCNF) is used for other models. All the models are solved for multiple randomly generated models of different problems to compare their computational efficiency.	1.385641	5

ex9: Instance-to-Instance Comparison Results

Parent Instance (ex9)

MIC Top 5 Instances

MIPLIB Top 5 Instances

Instance Summary

ex9: Instance-to-Model Comparison Results

MIC Top 5 Model Groups

Model Group Summary