Instance - assign1-10-4


	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	eilC76-2 [MIPLIB]	eilA101-2 [MIPLIB]	neos-3352863-ancoa [MIPLIB]	pythago7825 [MIPLIB]	pythago7824 [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 / 0.801	2 / 0.860	3 / 0.862	4 / 0.907	5 / 0.907
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	bppc8-09 [MIPLIB]	bppc4-08 [MIPLIB]	assign1-5-8 [MIPLIB]	bppc6-02 [MIPLIB]	rlp1 [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.	75 / 1.588	85 / 1.610	89 / 1.619	184 / 1.965	745 / 2.551
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 assign1-10-4, the five most similar instances to assign1-10-4 according to the MIC, and the five most similar instances to assign1-10-4 according to MIPLIB 2017.

	INSTANCE	SUBMITTER	DESCRIPTION	ISS	RANK
Parent Instance	assign1-10-4 [MIPLIB]	Robert Fourer	Imported from the MIPLIB2010 submissions.	0.000000	-
MIC Top 5	eilC76-2 [MIPLIB]	J. Linderoth	Set partitioning problem approximation for capicated vehicle routing problem instance from TSPLIB Imported from the MIPLIB2010 submissions.	0.800815	1
	eilA101-2 [MIPLIB]	J. Linderoth	Set partitioning problem approximation for capicated vehicle routing problem instance from TSPLIB	0.859703	2
	neos-3352863-ancoa [MIPLIB]	Jeff Linderoth	(None provided)	0.861812	3
	pythago7825 [MIPLIB]	Felix J. L. Willamowski	2-coloring of Pythagorean triples	0.906999	4
	pythago7824 [MIPLIB]	Felix J. L. Willamowski	2-coloring of Pythagorean triples	0.907135	5
MIPLIB Top 5	bppc8-09 [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).	1.588059	75
	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).	1.610238	85
	assign1-5-8 [MIPLIB]	Robert Fourer	Imported from the MIPLIB2010 submissions.	1.619376	89
	bppc6-02 [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).	1.964628	184
	rlp1 [MIPLIB]	MIPLIB submission pool	Imported from the MIPLIB2010 submissions.	2.550855	745

These are model group composite (MGC) images for the MIC top 5 model groups.
Name	assign1	f2gap	generated	2hopcds	independentset
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 / 0.562	2 / 0.932	3 / 0.946	4 / 1.021	5 / 1.023

Model Group Summary

The table below contains summary information for the five most similar model groups to assign1-10-4 according to the MIC.

	MODEL GROUP	SUBMITTER	DESCRIPTION	ISS	RANK
MIC Top 5	assign1	Robert Fourer	Imported from the MIPLIB2010 submissions.	0.561721	1
	f2gap	Salim Haddadi	Restrictions of well-known hard generalized assignment problem models (D10400,D20400,D40400,D15900,D30900,D60900,D201600,D401600,D801600)	0.932332	2
	generated	Simon Bowly	Randomly generated integer and binary programming models. These results are part of an early phase of work aimed at generating diverse and challenging MIP models for experimental testing. We have aimed to produce small integer and binary programming models which are reasonably difficult to solve and have varied structure, eliciting a range of behaviour in state of the art algorithms.	0.946282	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.	1.020637	4
	independentset	Toni Sorrell	These models are based on Neil Sloane's Challenge problems: Independent Sets in Graphs.	1.022916	5

Type:	Instance
Submitter:	Robert Fourer
Description:	Imported from the MIPLIB2010 submissions.
	MIPLIB Entry

Model Group Assignment from MIPLIB:	assign1
Assigned Model Group Rank/ISS in the MIC:	1 / 0.561

assign1-10-4: Instance-to-Instance Comparison Results

Parent Instance (assign1-10-4)

MIC Top 5 Instances

MIPLIB Top 5 Instances

Instance Summary

assign1-10-4: Instance-to-Model Comparison Results

MIC Top 5 Model Groups

Model Group Summary