Instance - bab2

bab2: Instance-to-Instance Comparison Results

Type:	Instance
Submitter:	Elmar Swarat
Description:	Vehicle Routing with profits and an integrated crew scheduling formulated by two coupled multi-commodity flow problems.
	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	eva1aprime6x6opt [MIPLIB]	bab5 [MIPLIB]	rwth-timetable [MIPLIB]	berlin_5_8_0 [MIPLIB]	ns2034125 [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 / 1.427	2 / 1.449	3 / 1.512	4 / 1.514	5 / 1.519
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	bab5 [MIPLIB]	n2seq36q [MIPLIB]	neos-3555904-turama [MIPLIB]	bab6 [MIPLIB]	bab3 [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.	2 / 1.449	186 / 1.889	485 / 1.991	550 / 2.022	573 / 2.030
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 bab2, the five most similar instances to bab2 according to the MIC, and the five most similar instances to bab2 according to MIPLIB 2017.

	INSTANCE	SUBMITTER	DESCRIPTION	ISS	RANK
Parent Instance	bab2 [MIPLIB]	Elmar Swarat	Vehicle Routing with profits and an integrated crew scheduling formulated by two coupled multi-commodity flow problems.	0.000000	-
MIC Top 5	eva1aprime6x6opt [MIPLIB]	Yoshihiro Kanno	MILP approach to generate structures with negative thermal expansion coefficients	1.426897	1
	bab5 [MIPLIB]	Elmar Swarat	Vehicle routing with profits and an integrated crew scheduling problem formulated by two coupled multi-commodity flow problems	1.449210	2
	rwth-timetable [MIPLIB]	Gerald Lach	University Course Timetabling from the RWTH Aachen	1.512198	3
	berlin_5_8_0 [MIPLIB]	G. Klau	Railway optimization problems. The problem was solved using CPLEX 12.3 on a 32 core Sun Galaxy 4600 machine, equipped with eight Quad-Core AMD Opteron 8384 processors at 2.7 GHz and 512 GB RAM. It took approximately 9 hours. The problem was solved using CPLEX 12.4 in about 55 minutes (May 2014).	1.514408	4
	ns2034125 [MIPLIB]	NEOS Server Submission	Imported from the MIPLIB2010 submissions.	1.519334	5
MIPLIB Top 5	bab5 [MIPLIB]	Elmar Swarat	Vehicle routing with profits and an integrated crew scheduling problem formulated by two coupled multi-commodity flow problems	1.449210	2
	n2seq36q [MIPLIB]	R. Meirich	Static line planning models on the Dutch IC network	1.889115	186
	neos-3555904-turama [MIPLIB]	Hans Mittelmann	Collection of anonymous submissions to the NEOS Server for Optimization	1.991449	485
	bab6 [MIPLIB]	Elmar Swarat	Vehicle routing with profit and an integrated crew scheduling like bab2 - bab5. Instances differ in multi-commodity-flow formulation (path oder arc formulation) or time discretization and some are quite easy to solve while others (bab2, bab3 and bab6) are very difficult.	2.022234	550
	bab3 [MIPLIB]	Elmar Swarat	Vehicle routing with profits and an integrated crew scheduling problem formulated by two coupled multi-commodity flow problems	2.029887	573

bab2: Instance-to-Model Comparison Results

Model Group Assignment from MIPLIB:	bab
Assigned Model Group Rank/ISS in the MIC:	166 / 3.149

These are model group composite (MGC) images for the MIC top 5 model groups.
Name	evaprime	huefner	lectsched	scp	neos-pseudoapplication-109
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 / 2.162	2 / 2.190	3 / 2.196	4 / 2.210	5 / 2.223

Model Group Summary

The table below contains summary information for the five most similar model groups to bab2 according to the MIC.

	MODEL GROUP	SUBMITTER	DESCRIPTION	ISS	RANK
MIC Top 5	evaprime	Yoshihiro Kanno	MILP approach to generate structures with negative thermal expansion coefficients	2.162455	1
	huefner	Falk Hueffner	The NP-hard Balanced Subgraph problem (variant of MaxCut) encoded as ILPs. Real-world models from two applications from bioinformatics, finding monotone subsystems in gene regulatory networks (http://dx.doi.org/10.1007/s10878-009-9212-2) and finding optimal layouts of tanglegrams (http://dx.doi.org/10.1007/978-3-642-11269-0).	2.190074	2
	lectsched	Harald Schilly	University lecture scheduling model	2.195952	3
	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	2.209554	4
	neos-pseudoapplication-109	Jeff Linderoth	(None provided)	2.223294	5

bab2: Instance-to-Instance Comparison Results

Parent Instance (bab2)

MIC Top 5 Instances

MIPLIB Top 5 Instances

Instance Summary

bab2: Instance-to-Model Comparison Results

MIC Top 5 Model Groups

Model Group Summary