Instance - sct1

sct1: Instance-to-Instance Comparison Results

Type:	Instance
Submitter:	Siemens
Description:	Assembly line balancing for printed circuit board production
	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	sct31 [MIPLIB]	neos5 [MIPLIB]	neos-3135526-osun [MIPLIB]	sct32 [MIPLIB]	physiciansched5-3 [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 / 1.223	2 / 1.370	3 / 1.373	4 / 1.430	5 / 1.431
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	sct31 [MIPLIB]	sct32 [MIPLIB]	sct2 [MIPLIB]	gus-sch [MIPLIB]	sct5 [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 / 1.223	4 / 1.430	693 / 2.260	726 / 2.269	772 / 2.281
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 sct1, the five most similar instances to sct1 according to the MIC, and the five most similar instances to sct1 according to MIPLIB 2017.

	INSTANCE	SUBMITTER	DESCRIPTION	ISS	RANK
Parent Instance	sct1 [MIPLIB]	Siemens	Assembly line balancing for printed circuit board production	0.000000	-
MIC Top 5	sct31 [MIPLIB]	Siemens	Assembly line balancing for printed circuit board production	1.223480	1
	neos5 [MIPLIB]	NEOS Server Submission	Imported from the MIPLIB2010 submissions.	1.370160	2
	neos-3135526-osun [MIPLIB]	Jeff Linderoth	Claimed infeasible by most solvers.	1.373330	3
	sct32 [MIPLIB]	Siemens	Assembly line balancing for printed circuit board production. First solved by Gurobi 7.0 in 65 hours (32 threads).	1.430129	4
	physiciansched5-3 [MIPLIB]	Pelin Damci-Kurt	Physician scheduling problem for hospitalist, radiology and kidney specialist groups.	1.430910	5
MIPLIB Top 5	sct31 [MIPLIB]	Siemens	Assembly line balancing for printed circuit board production	1.223480	1
	sct32 [MIPLIB]	Siemens	Assembly line balancing for printed circuit board production. First solved by Gurobi 7.0 in 65 hours (32 threads).	1.430129	4
	sct2 [MIPLIB]	Siemens	Assembly line balancing for printed circuit board production	2.260493	693
	gus-sch [MIPLIB]	Alexandra M. Newman	course scheduling model	2.269156	726
	sct5 [MIPLIB]	Siemens	Assembly line balancing for printed circuit board production	2.281430	772

sct1: Instance-to-Model Comparison Results

Model Group Assignment from MIPLIB:	sct
Assigned Model Group Rank/ISS in the MIC:	45 / 2.339

These are model group composite (MGC) images for the MIC top 5 model groups.
Name	neos-pseudoapplication-21	generated	scp	independentset	neos-pseudoapplication-101
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 / 1.632	2 / 1.708	3 / 1.729	4 / 1.757	5 / 1.845

Model Group Summary

The table below contains summary information for the five most similar model groups to sct1 according to the MIC.

	MODEL GROUP	SUBMITTER	DESCRIPTION	ISS	RANK
MIC Top 5	neos-pseudoapplication-21	NEOS Server Submission	Imported from the MIPLIB2010 submissions.	1.631509	1
	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.	1.708135	2
	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	1.728612	3
	independentset	Toni Sorrell	These models are based on Neil Sloane's Challenge problems: Independent Sets in Graphs.	1.757133	4
	neos-pseudoapplication-101	NEOS Server Submission	Model coming from the NEOS Server with unknown application. Infeasibility claimed by CPLEX 12.6 and CPLEX 12.6.1 with extreme numerical caution emphasi after 4 and 2 hours computation, respectively.	1.844959	5

sct1: Instance-to-Instance Comparison Results

Parent Instance (sct1)

MIC Top 5 Instances

MIPLIB Top 5 Instances

Instance Summary

sct1: Instance-to-Model Comparison Results

MIC Top 5 Model Groups

Model Group Summary