Instance - core4284-1064


	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	core2536-691 [MIPLIB]	scpk4 [MIPLIB]	v150d30-2hopcds [MIPLIB]	sorrell4 [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 / 0.760	3 / 0.762	4 / 0.764	5 / 0.786
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	core2536-691 [MIPLIB]	rail507 [MIPLIB]	core2586-950 [MIPLIB]	core4872-1529 [MIPLIB]	ex1010-pi [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	13 / 0.979	14 / 0.982	27 / 1.141	167 / 2.205
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 core4284-1064, the five most similar instances to core4284-1064 according to the MIC, and the five most similar instances to core4284-1064 according to MIPLIB 2017.

	INSTANCE	SUBMITTER	DESCRIPTION	ISS	RANK
Parent Instance	core4284-1064 [MIPLIB]	A. Caprara, M. Fischetti, P. Toth	Set covering instance coming from Italian railway models	0.000000	-
MIC Top 5	core2536-691 [MIPLIB]	A. Caprara, M. Fischetti, P. Toth	Set covering instance coming from Italian railway models	0.735801	1
	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	0.760313	2
	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.	0.762239	3
	sorrell4 [MIPLIB]	Toni Sorrell	These instances are based on Neil Sloane's Challenge problems: Independent Sets in Graphs.	0.764282	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	0.786178	5
MIPLIB Top 5	core2536-691 [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	0.979429	13
	core2586-950 [MIPLIB]	A. Caprara, M. Fischetti, P. Toth	Set covering instance coming from Italian railway models	0.982304	14
	core4872-1529 [MIPLIB]	A. Caprara, M. Fischetti, P. Toth	Set covering instance coming from Italian railway models	1.140869	27
	ex1010-pi [MIPLIB]	M. Winkler	Logic synthesis problem from the 2010 SAT conference pseudo-Boolean competition	2.204814	167

These are model group composite (MGC) images for the MIC top 5 model groups.
Name	iis	neos-pseudoapplication-106	air	ivu	reblock
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 / 0.967	2 / 1.039	3 / 1.082	4 / 1.090	5 / 1.097

Model Group Summary

The table below contains summary information for the five most similar model groups to core4284-1064 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.	0.966997	1
	neos-pseudoapplication-106	Hans Mittelmann	Collection of anonymous submissions to the NEOS Server for Optimization	1.038571	2
	air	G. Astfalk	Airline crew scheduling set partitioning problem	1.082199	3
	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.	1.090374	4
	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.	1.097277	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:	9 / 1.296

core4284-1064: Instance-to-Instance Comparison Results

Parent Instance (core4284-1064)

MIC Top 5 Instances

MIPLIB Top 5 Instances

Instance Summary

core4284-1064: Instance-to-Model Comparison Results

MIC Top 5 Model Groups

Model Group Summary