Instance - gus-sch

gus-sch: Instance-to-Instance Comparison Results

Type:	Instance
Submitter:	Alexandra M. Newman
Description:	course scheduling model
	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	nu120-pr12 [MIPLIB]	nu4-pr9 [MIPLIB]	ns4-pr6 [MIPLIB]	aflow40b [MIPLIB]	neos-827175 [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 / 0.347	2 / 0.353	3 / 0.360	4 / 0.375	5 / 0.382
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	mkc [MIPLIB]	comp08-2idx [MIPLIB]	neos-555343 [MIPLIB]	qiu [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.	34 / 0.496	49 / 0.540	66 / 0.603	216 / 1.088	273 / 1.209
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 gus-sch, the five most similar instances to gus-sch according to the MIC, and the five most similar instances to gus-sch according to MIPLIB 2017.

	INSTANCE	SUBMITTER	DESCRIPTION	ISS	RANK
Parent Instance	gus-sch [MIPLIB]	Alexandra M. Newman	course scheduling model	0.000000	-
MIC Top 5	nu120-pr12 [MIPLIB]	MIPLIB submission pool	Imported from the MIPLIB2010 submissions.	0.346579	1
	nu4-pr9 [MIPLIB]	MIPLIB submission pool	Imported from the MIPLIB2010 submissions.	0.353225	2
	ns4-pr6 [MIPLIB]	MIPLIB submission pool	Imported from the MIPLIB2010 submissions.	0.359659	3
	aflow40b [MIPLIB]	T. Achterberg	Arborescence flow problem on a graph with 40 nodes and edge density 0.9	0.375131	4
	neos-827175 [MIPLIB]	NEOS Server Submission	Imported from the MIPLIB2010 submissions.	0.382480	5
MIPLIB Top 5	mkc [MIPLIB]	J. Kalagnanam, M. Dawande	Multiple knapsack problem with color constraints. John Forrest, Laszlo Ladanyi and Jayant Kalagnanam solved this instance by reformulation in 1999.	0.495574	34
	comp08-2idx [MIPLIB]	Matias Sørensen	Instances comp01-21 of curriculum based course timetabling from the International Timetabling Competition 2007. These are time-assignment models (Stage I of the decomposed model), which are smaller than the full model, but still hard to solve.	0.540208	49
	neos-555343 [MIPLIB]	NEOS Server Submission	Imported from the MIPLIB2010 submissions.	0.602589	66
	qiu [MIPLIB]	Y. Chiu, J. Eckstein	Fiber-optic network design, logical SONET ring level	1.088197	216
	sct5 [MIPLIB]	Siemens	Assembly line balancing for printed circuit board production	1.208793	273

gus-sch: 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	nus-prxy	aflow	neos-pseudoapplication-60	ab	radiation
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 / 0.608	2 / 0.937	3 / 0.946	4 / 0.984	5 / 0.997

Model Group Summary

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

	MODEL GROUP	SUBMITTER	DESCRIPTION	ISS	RANK
MIC Top 5	nus-prxy	MIPLIB submission pool	Imported from the MIPLIB2010 submissions.	0.607610	1
	aflow	T. Achterberg	Arborescence flow problem on a graph with 40 nodes and edge density 0.9	0.936546	2
	neos-pseudoapplication-60	NEOS Server Submission	Model coming from the NEOS Server with unknown application	0.945797	3
	ab	MIPLIB submission pool	Imported from the MIPLIB2010 submissions.	0.984284	4
	radiation	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	0.997193	5

gus-sch: Instance-to-Instance Comparison Results

Parent Instance (gus-sch)

MIC Top 5 Instances

MIPLIB Top 5 Instances

Instance Summary

gus-sch: Instance-to-Model Comparison Results

MIC Top 5 Model Groups

Model Group Summary