Instance - lectsched-1

lectsched-1: Instance-to-Instance Comparison Results

Type:	Instance
Submitter:	Harald Schilly
Description:	University lecture scheduling instance
	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	lectsched-3 [MIPLIB]	lectsched-2 [MIPLIB]	lectsched-5-obj [MIPLIB]	probportfolio [MIPLIB]	tanglegram6 [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 / 0.256	2 / 0.362	3 / 0.364	4 / 0.682	5 / 0.719
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	lectsched-3 [MIPLIB]	lectsched-2 [MIPLIB]	neos-3355323-arnon [MIPLIB]	neos-3211096-shag [MIPLIB]	neos-3603137-hoteo [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 / 0.256	2 / 0.362	357 / 1.527	505 / 1.652	802 / 2.197
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 lectsched-1, the five most similar instances to lectsched-1 according to the MIC, and the five most similar instances to lectsched-1 according to MIPLIB 2017.

	INSTANCE	SUBMITTER	DESCRIPTION	ISS	RANK
Parent Instance	lectsched-1 [MIPLIB]	Harald Schilly	University lecture scheduling instance	0.000000	-
MIC Top 5	lectsched-3 [MIPLIB]	Harald Schilly	University lecture scheduling instance	0.256305	1
	lectsched-2 [MIPLIB]	Harald Schilly	University lecture scheduling instance	0.362304	2
	lectsched-5-obj [MIPLIB]	Harald Schilly	scheduling lectures at university - smaller subset of data with objective to minimize certain overlappings	0.364403	3
	probportfolio [MIPLIB]	Feng Qiu	Sample average approximation formulation of a probabilistic portfolio optimization problem. Solved using ug[SCIP/spx], a distributed massively parallel version of SCIP run on 2,000 cores at the HLRN-II super computer facility.	0.681776	4
	tanglegram6 [MIPLIB]	Falk Hueffner	The NP-hard Balanced Subgraph problem (variant of MaxCut) encoded as ILPs. Real-world instances 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).	0.718930	5
MIPLIB Top 5	lectsched-3 [MIPLIB]	Harald Schilly	University lecture scheduling instance	0.256305	1
	lectsched-2 [MIPLIB]	Harald Schilly	University lecture scheduling instance	0.362304	2
	neos-3355323-arnon [MIPLIB]	Jeff Linderoth	(None provided)	1.527081	357
	neos-3211096-shag [MIPLIB]	Jeff Linderoth	Solved with status infeasible by ParaSCIP in 42484 sec.\xa0It was confirmed by ParaXpress.	1.652191	505
	neos-3603137-hoteo [MIPLIB]	Jeff Linderoth	(None provided)	2.196771	802

lectsched-1: Instance-to-Model Comparison Results

Model Group Assignment from MIPLIB:	lectsched
Assigned Model Group Rank/ISS in the MIC:	2 / 1.288

These are model group composite (MGC) images for the MIC top 5 model groups.
Name	neos-pseudoapplication-109	lectsched	map	rmatr	polygonpack
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 / 1.279	2 / 1.289	3 / 1.357	4 / 1.389	5 / 1.396

Model Group Summary

The table below contains summary information for the five most similar model groups to lectsched-1 according to the MIC.

	MODEL GROUP	SUBMITTER	DESCRIPTION	ISS	RANK
MIC Top 5	neos-pseudoapplication-109	Jeff Linderoth	(None provided)	1.279242	1
	lectsched	Harald Schilly	University lecture scheduling model	1.288720	2
	map	Kiyan Ahmadizadeh	Land parcel selection problems motivated by Red-Cockaded Woodpecker conservation problem	1.357426	3
	rmatr	Dmitry Krushinsky	Model coming from a formulation of the p-Median problem using square cost matrices	1.389253	4
	polygonpack	Antonio Frangioni	Given a set P of polygons, not necessarily convex, and a rectangle, we want to find the subset S of P with largest possible total area and a position every p in S so that there are no overlaps and they are all included in the rectangle. We allow a small set of rotations (0, 90, 180, 270 degrees) for every polygon. The problem is simplified w.r.t. the real application because the polygons do not have (fully encircled) "holes", which are supposedly filled-in separately, although they can have "bays". Models are saved as .lp. Model LpPackingModel_Dim means that we are trying to pack polygons taken from set ; there are currently 5 different sets, and is 7, 10 or 15.	1.395553	5

lectsched-1: Instance-to-Instance Comparison Results

Parent Instance (lectsched-1)

MIC Top 5 Instances

MIPLIB Top 5 Instances

Instance Summary

lectsched-1: Instance-to-Model Comparison Results

MIC Top 5 Model Groups

Model Group Summary