Instance - tbfp-bigm

tbfp-bigm: 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	rococoC11-010100 [MIPLIB]	rococoC12-010001 [MIPLIB]	rococoB10-011000 [MIPLIB]	rococoC10-001000 [MIPLIB]	rococoC11-011100 [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 / 0.638	2 / 0.749	3 / 0.833	4 / 0.935	5 / 0.983
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-5041756-cobark [MIPLIB]	ns1760995 [MIPLIB]	graphdraw-domain [MIPLIB]	pw-myciel4 [MIPLIB]	neos-1171448 [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.	80 / 1.218	138 / 1.276	425 / 1.555	779 / 2.074	980 / 3.598
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-bigm, the five most similar instances to tbfp-bigm according to the MIC, and the five most similar instances to tbfp-bigm according to MIPLIB 2017.

	INSTANCE	SUBMITTER	DESCRIPTION	ISS	RANK
Parent Instance	tbfp-bigm [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	rococoC11-010100 [MIPLIB]	A. Chabrier, E. Danna, C. Le Pape, L. Perron	Model for dimensioning the arc capacities in a telecommunication network.	0.638024	1
	rococoC12-010001 [MIPLIB]	A. Chabrier, E. Danna, C. Le Pape, L. Perron	Model for dimensioning the arc capacities in a telecommunication network.	0.749019	2
	rococoB10-011000 [MIPLIB]	A. Chabrier, E. Danna, C. Le Pape, L. Perron	Model for dimensioning the arc capacities in a telecommunication network	0.832846	3
	rococoC10-001000 [MIPLIB]	A. Chabrier, E. Danna, C. Le Pape, L. Perron	Model for dimensioning the arc capacities in a telecommunication network	0.935046	4
	rococoC11-011100 [MIPLIB]	A. Chabrier, E. Danna, C. Le Pape, L. Perron	Model for dimensioning the arc capacities in a telecommunication network. Solved by Gurobi 4.5.1 (4 threads) in 66892.47 seconds.	0.982787	5
MIPLIB Top 5	neos-5041756-cobark [MIPLIB]	Jeff Linderoth	(None provided)	1.217748	80
	ns1760995 [MIPLIB]	NEOS Server Submission	Instance coming from the NEOS Server with unknown application.	1.275633	138
	graphdraw-domain [MIPLIB]	Cézar Augusto Nascimento e Silva	In the Graph Drawing problem a set of symbols must be placed in a plane and their connections routed. The objective is to produce aesthetically pleasant, easy to read diagrams. As a primary concern one usually tries to minimize edges crossing, edges' length, waste of space and number of bents in the connections. When formulated with these constraints the problem becomes NP-Hard . In practice many additional complicating requirements can be included, such as non-uniform sizes for symbols. Thus, some heuristics such as the generalized force-direct method and Simulated Annealing have been proposed to tackle this problem. uses a grid structure to approach the Entity-Relationship (ER) drawing problem, emphasizing the differences between ER drawing and the more classical circuit drawing problems. presented different ways of producing graph layouts (e.g.: tree, orthogonal, visibility representations, hierarchic, among others) for general graphs with applications on different subjects. The ability to automatically produce high quality layouts is very important in many applications, one of these is Software Engineering: the availability of easy to understand ER diagrams, for instance, can improve the time needed for developers to master database models and increase their productivity. Our solution approach involves two phases: (\\(i\\)) firstly the optimal placement of entities is solved, i.e.: entities are positioned so as to minimize the distances between connected entities; and (\\(ii\\)) secondly, edges are routed minimizing bends and avoiding the inclusion of connectors too close. We present the model for the first phase of our problem.	1.555449	425
	pw-myciel4 [MIPLIB]	Arie Koster	Model to compute the pathwidth of Mycielski-4 instance from DIMACS graph coloring database	2.073973	779
	neos-1171448 [MIPLIB]	NEOS Server Submission	Imported from the MIPLIB2010 submissions.	3.597764	980

tbfp-bigm: 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	rococo	map	ustun	rmatr	allcolor
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 / 1.525	2 / 1.563	3 / 1.571	4 / 1.574	5 / 1.648

Model Group Summary

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

	MODEL GROUP	SUBMITTER	DESCRIPTION	ISS	RANK
MIC Top 5	rococo	A. Chabrier, E. Danna, C. Le Pape, L. Perron	Model for dimensioning the arc capacities in a telecommunication network. Solved by Gurobi 4.5.1 (4 threads) in 66892.47 seconds.	1.524680	1
	map	Kiyan Ahmadizadeh	Land parcel selection problems motivated by Red-Cockaded Woodpecker conservation problem	1.562523	2
	ustun	Berk Ustun	MIP to create optimized data-driven scoring systems. See: https://github.com/ustunb/miplib2017-slim#miplib2017-slim for a description.	1.570553	3
	rmatr	Dmitry Krushinsky	Model coming from a formulation of the p-Median problem using square cost matrices	1.573670	4
	allcolor	Domenico Salvagnin	Prepack optimization model.	1.648064	5

tbfp-bigm: Instance-to-Instance Comparison Results

Parent Instance (tbfp-bigm)

MIC Top 5 Instances

MIPLIB Top 5 Instances

Instance Summary

tbfp-bigm: Instance-to-Model Comparison Results

MIC Top 5 Model Groups

Model Group Summary