Instance - tbfp-network

tbfp-network: Instance-to-Instance Comparison Results

Type:	Instance
Submitter:	Rob Pratt
Description:	Two formulations (big-M and network-based) for traveling baseball fan problem. Uses data from 2014 Major League Baseball regular season. Paper uses 2014 data: http://support.sas.com/resources/papers/proceedings14/SAS101-2014.pdf Blog post uses 2015 data: http://blogs.sas.com/content/operations/2015/04/03/the-traveling-baseball-fan-problem/
	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	neos-3581454-haast [MIPLIB]	allcolor10 [MIPLIB]	allcolor58 [MIPLIB]	neos-941313 [MIPLIB]	unitcal_7 [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 / 0.760	2 / 0.763	3 / 0.766	4 / 0.767	5 / 0.773
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	neos-4531126-vouga [MIPLIB]	s100 [MIPLIB]	supportcase6 [MIPLIB]	datt256 [MIPLIB]	nu120-pr9* [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.	39 / 0.928	411 / 1.557	965 / 3.167	972 / 3.278	188* / 1.196*
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 tbfp-network, the five most similar instances to tbfp-network according to the MIC, and the five most similar instances to tbfp-network according to MIPLIB 2017.

	INSTANCE	SUBMITTER	DESCRIPTION	ISS	RANK
Parent Instance	tbfp-network [MIPLIB]	Rob Pratt	Two formulations (big-M and network-based) for traveling baseball fan problem. Uses data from 2014 Major League Baseball regular season. Paper uses 2014 data: http://support.sas.com/resources/papers/proceedings14/SAS101-2014.pdf Blog post uses 2015 data: http://blogs.sas.com/content/operations/2015/04/03/the-traveling-baseball-fan-problem/	0.000000	-
MIC Top 5	neos-3581454-haast [MIPLIB]	Jeff Linderoth	(None provided)	0.759749	1
	allcolor10 [MIPLIB]	Domenico Salvagnin	Prepack optimization instance.	0.762502	2
	allcolor58 [MIPLIB]	Domenico Salvagnin	Prepack optimization model.	0.766126	3
	neos-941313 [MIPLIB]	NEOS Server Submission	Instance coming from the NEOS Server with unknown application	0.766790	4
	unitcal_7 [MIPLIB]	R. O’Neill	California seven day unit commitment problem	0.773209	5
MIPLIB Top 5	neos-4531126-vouga [MIPLIB]	Jeff Linderoth	(None provided)	0.928041	39
	s100 [MIPLIB]	Daniel Espinoza	Wine Scheduling problem with 100 jobs and four processing machines	1.557418	411
	supportcase6 [MIPLIB]	Michael Winkler	MIP instances collected from Gurobi forum with unknown application	3.167296	965
	datt256 [MIPLIB]	Jon Dattorro	Model to find solution to the ``Eternity II'' puzzle	3.277904	972
	nu120-pr9* [MIPLIB]	MIPLIB submission pool	Imported from the MIPLIB2010 submissions.	1.196344*	188*

tbfp-network: 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	sing	polygonpack	allcolor	neos-pseudoapplication-27	neos-pseudoapplication-14
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 / 0.980	2 / 0.991	3 / 1.051	4 / 1.097	5 / 1.161

Model Group Summary

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

	MODEL GROUP	SUBMITTER	DESCRIPTION	ISS	RANK
MIC Top 5	sing	Daniel Espinoza	Imported from the MIPLIB2010 submissions.	0.979751	1
	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.	0.991402	2
	allcolor	Domenico Salvagnin	Prepack optimization model.	1.050902	3
	neos-pseudoapplication-27	NEOS Server Submission	Imported from the MIPLIB2010 submissions.	1.097261	4
	neos-pseudoapplication-14	Jeff Linderoth	(None provided)	1.161318	5

tbfp-network: Instance-to-Instance Comparison Results

Parent Instance (tbfp-network)

MIC Top 5 Instances

MIPLIB Top 5 Instances

Instance Summary

tbfp-network: Instance-to-Model Comparison Results

MIC Top 5 Model Groups

Model Group Summary