Instance - ic97

ic97_potential: Instance-to-Instance Comparison Results

Type:	Instance
Submitter:	L. Peeters
Description:	A model for cyclic railway timetable optimization
	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-3610040-iskar [MIPLIB]	neos-3611447-jijia [MIPLIB]	neos-3611689-kaihu [MIPLIB]	neos-3610051-istra [MIPLIB]	neos-3610173-itata [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 / 0.919	2 / 0.924	3 / 0.954	4 / 1.012	5 / 1.032
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	supportcase26 [MIPLIB]	icir97_potential [MIPLIB]	neos-5115478-kaveri [MIPLIB]	timtab1 [MIPLIB]	neos-5107597-kakapo* [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.	7 / 1.123	12 / 1.163	40 / 1.255	86 / 1.324	40* / 1.255*
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 ic97_potential, the five most similar instances to ic97_potential according to the MIC, and the five most similar instances to ic97_potential according to MIPLIB 2017.

	INSTANCE	SUBMITTER	DESCRIPTION	ISS	RANK
Parent Instance	ic97_potential [MIPLIB]	L. Peeters	A model for cyclic railway timetable optimization	0.000000	-
MIC Top 5	neos-3610040-iskar [MIPLIB]	Jeff Linderoth	(None provided)	0.919261	1
	neos-3611447-jijia [MIPLIB]	Jeff Linderoth	(None provided)	0.923541	2
	neos-3611689-kaihu [MIPLIB]	Jeff Linderoth	(None provided)	0.954052	3
	neos-3610051-istra [MIPLIB]	Jeff Linderoth	(None provided)	1.012218	4
	neos-3610173-itata [MIPLIB]	Jeff Linderoth	(None provided)	1.031962	5
MIPLIB Top 5	supportcase26 [MIPLIB]	Michael Winkler	MIP instances collected from Gurobi forum with unknown application	1.122880	7
	icir97_potential [MIPLIB]	MIPLIB submission pool	Imported from the MIPLIB2010 submissions.	1.162983	12
	neos-5115478-kaveri [MIPLIB]	Jeff Linderoth	(None provided)	1.254551	40
	timtab1 [MIPLIB]	C. Liebchen, R. Möhring	Public transport scheduling problem	1.323844	86
	neos-5107597-kakapo* [MIPLIB]	Jeff Linderoth	(None provided)	1.254551*	40*

ic97_potential: 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	scp	hypothyroid	neos-pseudoapplication-91	stein	supportvectormachine
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 / 1.482	2 / 1.485	3 / 1.538	4 / 1.539	5 / 1.620

Model Group Summary

The table below contains summary information for the five most similar model groups to ic97_potential according to the MIC.

	MODEL GROUP	SUBMITTER	DESCRIPTION	ISS	RANK
MIC Top 5	scp	Shunji Umetani	This is a random test model 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 models. We have also generated reduced models 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 model generator program from the following web site. https://sites.google.com/site/shunjiumetani/benchmark	1.481548	1
	hypothyroid	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	1.485353	2
	neos-pseudoapplication-91	Jeff Linderoth	(None provided)	1.538359	3
	stein	MIPLIB submission pool	Imported from the MIPLIB2010 submissions.	1.539111	4
	supportvectormachine	Toni Sorrell	Suport vector machine with ramp loss. GSVM2-RL is the formulation found in Hess E. and Brooks P. (2015) paper, The Support Vector Machine and Mixed Integer Linear Programming: Ramp Loss SVM with L1-Norm Regularization	1.619601	5

ic97_potential: Instance-to-Instance Comparison Results

Parent Instance (ic97_potential)

MIC Top 5 Instances

MIPLIB Top 5 Instances

Instance Summary

ic97_potential: Instance-to-Model Comparison Results

MIC Top 5 Model Groups

Model Group Summary