Instance - dano3mip

dano3mip: Instance-to-Instance Comparison Results

Type:	Instance
Submitter:	Daniel Bienstock
Description:	Telecommunications applications
	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	dano3_3 [MIPLIB]	dano3_5 [MIPLIB]	bppc8-09 [MIPLIB]	neos-5045105-creuse [MIPLIB]	disctom [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 / 0.476	2 / 0.549	3 / 1.695	4 / 1.707	5 / 1.712
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	dano3_3 [MIPLIB]	dano3_5 [MIPLIB]	misc04inf [MIPLIB]	ns1111636 [MIPLIB]	set3-09* [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 / 0.476	2 / 0.549	224 / 2.507	824 / 2.991	380* / 2.683*
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 dano3mip, the five most similar instances to dano3mip according to the MIC, and the five most similar instances to dano3mip according to MIPLIB 2017.

	INSTANCE	SUBMITTER	DESCRIPTION	ISS	RANK
Parent Instance	dano3mip [MIPLIB]	Daniel Bienstock	Telecommunications applications	0.000000	-
MIC Top 5	dano3_3 [MIPLIB]	Daniel Bienstock	Telecommunications applications	0.476043	1
	dano3_5 [MIPLIB]	Daniel Bienstock	Telecommunications applications	0.548643	2
	bppc8-09 [MIPLIB]	Manuel Iori	The models that we attach solve the "bar-relaxation", also known as the "Bin Packing Problem with Contiguity" or the "P\|\|Cmax with contiguity". This is one of the most interesting relaxations for two dimensional cutting and packing problems. Its solution by means of an ILP software is the bottleneck of the primal decomposition methods that we attempted in the paper cited below. In detail, the files correspond to model (12)-(15) in the paper, applied to the instances of the Classes 4, 6 and 8 by Martello and Vigo (Management Science, 1998).	1.694511	3
	neos-5045105-creuse [MIPLIB]	Jeff Linderoth	(None provided)	1.707325	4
	disctom [MIPLIB]	MIPLIB submission pool	Imported from the MIPLIB2010 submissions.	1.712196	5
MIPLIB Top 5	dano3_3 [MIPLIB]	Daniel Bienstock	Telecommunications applications	0.476043	1
	dano3_5 [MIPLIB]	Daniel Bienstock	Telecommunications applications	0.548643	2
	misc04inf [MIPLIB]	MIPLIB submission pool	Imported from the MIPLIB2010 submissions.	2.506738	224
	ns1111636 [MIPLIB]	NEOS Server Submission	Network routing problem. Solved in June 2013 by CPLEX 12.5.1 with 32 threads in about 102 hours.	2.991495	824
	set3-09* [MIPLIB]	Kerem Akartunali	This is joint work with Andrew J. Miller, Universite de Bordeaux 1; RealOpt, INRIA Bordeaux Sud-Ouest, France. Andrew.Miller@math.u-bordeaux1.fr. These are five hard instances chosen from our library MULTILSB (Multi-item Lot-Sizing with Backlogging), which is fully available at (incl. documentation and mosel file):http://personal.strath.ac.uk/kerem.akartunali/research/multi-lsb/ For these 5 instances, gaps remain in the range of >50% after 30 min. (using latest version of FICO on a laptop with i7 processor and 4GB RAM): (first two columns indicate the 30 min-runs, and the last column indicates the best solutions we know at the moment). Computational results for these instances as well as for others of MULTILSB can be found on the website.	2.682596*	380*

dano3mip: Instance-to-Model Comparison Results

Model Group Assignment from MIPLIB:	dano
Assigned Model Group Rank/ISS in the MIC:	1 / 1.459

These are model group composite (MGC) images for the MIC top 5 model groups.
Name	dano	f2gap	neos-pseudoapplication-52	neos-pseudoapplication-78	mine
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 / 1.460	2 / 2.534	3 / 2.564	4 / 2.585	5 / 2.615

Model Group Summary

The table below contains summary information for the five most similar model groups to dano3mip according to the MIC.

	MODEL GROUP	SUBMITTER	DESCRIPTION	ISS	RANK
MIC Top 5	dano	Daniel Bienstock	Telecommunications applications	1.459614	1
	f2gap	Salim Haddadi	Restrictions of well-known hard generalized assignment problem models (D10400,D20400,D40400,D15900,D30900,D60900,D201600,D401600,D801600)	2.533988	2
	neos-pseudoapplication-52	Jeff Linderoth	(None provided)	2.564151	3
	neos-pseudoapplication-78	Jeff Linderoth	(None provided)	2.585145	4
	mine	Andreas Bley	Multi-period mine production scheduling model	2.615369	5

dano3mip: Instance-to-Instance Comparison Results

Parent Instance (dano3mip)

MIC Top 5 Instances

MIPLIB Top 5 Instances

Instance Summary

dano3mip: Instance-to-Model Comparison Results

MIC Top 5 Model Groups

Model Group Summary