Instance - core2536-691


	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	core4284-1064 [MIPLIB]	v150d30-2hopcds [MIPLIB]	sorrell4 [MIPLIB]	scpk4 [MIPLIB]	scpj4scip [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 / 0.736	2 / 0.747	3 / 0.750	4 / 0.750	5 / 0.777
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	core4284-1064 [MIPLIB]	rail507 [MIPLIB]	fast0507 [MIPLIB]	core2586-950 [MIPLIB]	core4872-1529 [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 / 0.736	7 / 0.914	8 / 0.918	12 / 0.929	28 / 1.160
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 core2536-691, the five most similar instances to core2536-691 according to the MIC, and the five most similar instances to core2536-691 according to MIPLIB 2017.

	INSTANCE	SUBMITTER	DESCRIPTION	ISS	RANK
Parent Instance	core2536-691 [MIPLIB]	A. Caprara, M. Fischetti, P. Toth	Set covering instance coming from Italian railway models	0.000000	-
MIC Top 5	core4284-1064 [MIPLIB]	A. Caprara, M. Fischetti, P. Toth	Set covering instance coming from Italian railway models	0.735801	1
	v150d30-2hopcds [MIPLIB]	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, instances with as few as 120 variables are left unsolved after one hour using Gurobi 7.0.2.	0.746644	2
	sorrell4 [MIPLIB]	Toni Sorrell	These instances are based on Neil Sloane's Challenge problems: Independent Sets in Graphs.	0.750026	3
	scpk4 [MIPLIB]	Shunji Umetani	This is a random test instance 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 instances. We have also generated reduced instances 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 instance generator program from the following web site. https://sites.google.com/site/shunjiumetani/benchmark	0.750124	4
	scpj4scip [MIPLIB]	Shunji Umetani	This is a random test instance 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 instances. We have also generated reduced instances 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 instance generator program from the following web site. https://sites.google.com/site/shunjiumetani/benchmark	0.776521	5
MIPLIB Top 5	core4284-1064 [MIPLIB]	A. Caprara, M. Fischetti, P. Toth	Set covering instance coming from Italian railway models	0.735801	1
	rail507 [MIPLIB]	A. Caprara, M. Fischetti, P. Toth	Railway crew scheduling	0.913912	7
	fast0507 [MIPLIB]	MIPLIB submission pool	Imported from the MIPLIB2010 submissions.	0.918381	8
	core2586-950 [MIPLIB]	A. Caprara, M. Fischetti, P. Toth	Set covering instance coming from Italian railway models	0.928663	12
	core4872-1529 [MIPLIB]	A. Caprara, M. Fischetti, P. Toth	Set covering instance coming from Italian railway models	1.160475	28

These are model group composite (MGC) images for the MIC top 5 model groups.
Name	iis	neos-pseudoapplication-106	air	neos-pseudoapplication-46	ivu
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 / 0.871	2 / 0.920	3 / 1.076	4 / 1.166	5 / 1.187

Model Group Summary

The table below contains summary information for the five most similar model groups to core2536-691 according to the MIC.

	MODEL GROUP	SUBMITTER	DESCRIPTION	ISS	RANK
MIC Top 5	iis	Marc Pfetsch	23 "middlehard" Set-Covering Models for MIPLIB: they have a small number of variables compared to the number of constraints and CPLEX 12.1 needs about one hour to solve them.For more information, have a look into the readme file which explains how the models can be created.	0.871384	1
	neos-pseudoapplication-106	Hans Mittelmann	Collection of anonymous submissions to the NEOS Server for Optimization	0.919825	2
	air	G. Astfalk	Airline crew scheduling set partitioning problem	1.076461	3
	neos-pseudoapplication-46	NEOS Server Submission	Imported from the MIPLIB2010 submissions.	1.165670	4
	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.	1.186809	5

Type:	Instance
Submitter:	A. Caprara, M. Fischetti, P. Toth
Description:	Set covering instance coming from Italian railway models
	MIPLIB Entry

Model Group Assignment from MIPLIB:	core
Assigned Model Group Rank/ISS in the MIC:	14 / 1.440

core2536-691: Instance-to-Instance Comparison Results

Parent Instance (core2536-691)

MIC Top 5 Instances

MIPLIB Top 5 Instances

Instance Summary

core2536-691: Instance-to-Model Comparison Results

MIC Top 5 Model Groups

Model Group Summary