Instance - neos-3661949-lesse


	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	bab6 [MIPLIB]	neos-2746589-doon [MIPLIB]	sct2 [MIPLIB]	gsvm2rl5 [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 other instances. A smaller ISS value indicates greater similarity.	1 / 1.129	2 / 1.179	3 / 1.201	4 / 1.203	5 / 1.248
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-1061020 [MIPLIB]	lr1dr04vc05v17a-t360 [MIPLIB]	lr1dr02vc05v8a-t360 [MIPLIB]	atlanta-ip [MIPLIB]	msc98-ip [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.	421 / 1.702	887 / 2.328	908 / 2.509	929 / 2.671	954 / 2.829
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 neos-3661949-lesse, the five most similar instances to neos-3661949-lesse according to the MIC, and the five most similar instances to neos-3661949-lesse according to MIPLIB 2017.

	INSTANCE	SUBMITTER	DESCRIPTION	ISS	RANK
Parent Instance	neos-3661949-lesse [MIPLIB]	Jeff Linderoth	(None provided)	0.000000	-
MIC Top 5	bab6 [MIPLIB]	Elmar Swarat	Vehicle routing with profit and an integrated crew scheduling like bab2 - bab5. Instances differ in multi-commodity-flow formulation (path oder arc formulation) or time discretization and some are quite easy to solve while others (bab2, bab3 and bab6) are very difficult.	1.128867	1
	neos-2746589-doon [MIPLIB]	Jeff Linderoth	(None provided)	1.179033	2
	sct2 [MIPLIB]	Siemens	Assembly line balancing for printed circuit board production	1.201324	3
	gsvm2rl5 [MIPLIB]	Toni Sorrell	Suport vector machine with ramp loss. GSVM2-RL is the formulation found in Hess E. and Brooks P. (2015) paper, The Support Vector Machine and Mixed Integer Linear Programming: Ramp Loss SVM with L1-Norm Regularization	1.203321	4
	sct5 [MIPLIB]	Siemens	Assembly line balancing for printed circuit board production	1.247532	5
MIPLIB Top 5	neos-1061020 [MIPLIB]	NEOS Server Submission	Imported from the MIPLIB2010 submissions.	1.702099	421
	lr1dr04vc05v17a-t360 [MIPLIB]	Dimitri Papageorgiou	Maritime Inventory Routing Problem Library - Group 2 Instances. These instances are available at https://mirplib.scl.gatech.edu/instances, along with a host of additional information such as the underlying data used to generate the model, best known upper and lower bounds, and more. There are three sets of 24 instances (for a total of 72 instances) with a planning horizon of 120, 180, and 360 time periods, respectively. As of March 2016, Cplex and Gurobi could only solve one or two to provably optimality in less than an hour.	2.328334	887
	lr1dr02vc05v8a-t360 [MIPLIB]	Dimitri Papageorgiou	Maritime Inventory Routing Problem Library - Group 2 Instances. These instances are available at https://mirplib.scl.gatech.edu/instances, along with a host of additional information such as the underlying data used to generate the model, best known upper and lower bounds, and more. There are three sets of 24 instances (for a total of 72 instances) with a planning horizon of 120, 180, and 360 time periods, respectively. As of March 2016, Cplex and Gurobi could only solve one or two to provably optimality in less than an hour.	2.509383	908
	atlanta-ip [MIPLIB]	E-Plus, D. Bienstock, A. Bley, R. Wessäly	Min-cost network dimensioning problems with a finite set of link capacities for each bidirected link, unsplittable shortest path routing, path restoration for single node failures, and routing path length restrictions	2.671345	929
	msc98-ip [MIPLIB]	E-Plus, D. Bienstock, A. Bley, R. Wessäly	Min-cost network dimensioning problems with a finite set of link capacities for each bidirected link, unsplittable shortest path routing, path restoration for single node failures, and routing path length restrictions	2.828549	954

These are model group composite (MGC) images for the MIC top 5 model groups.
Name	scp	square	neos-pseudoapplication-4	neos-pseudoapplication-109	supportvectormachine
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 / 1.866	2 / 1.873	3 / 1.874	4 / 1.884	5 / 1.886

Model Group Summary

The table below contains summary information for the five most similar model groups to neos-3661949-lesse according to the MIC.

	MODEL GROUP	SUBMITTER	DESCRIPTION	ISS	RANK
MIC Top 5	scp	Shunji Umetani	This is a random test model generator for SCP using the scheme of the following paper, namely the column cost c[j] are integer randomly generated from [1,100]; every column covers at least one row; and every row is covered by at least two columns. see reference: E. Balas and A. Ho, Set covering algorithms using cutting planes, heuristics, and subgradient optimization: A computational study, Mathematical Programming, 12 (1980), 37-60. We have newly generated Classes I-N with the following parameter values, where each class has five models. We have also generated reduced models by a standard pricing method in the following paper: S. Umetani and M. Yagiura, Relaxation heuristics for the set covering problem, Journal of the Operations Research Society of Japan, 50 (2007), 350-375. You can obtain the model generator program from the following web site. https://sites.google.com/site/shunjiumetani/benchmark	1.866316	1
	square	Sascha Kurz	Squaring the square For a given integer n, determine the minimum number of squares in a tiling of an \\(n\\times n\\) square using using only integer sided squares of smaller size. (Although the models get quite large even for moderate n, they can be solved to optimality for all \\(n \\le 61\\), while challenging the MIP solver, especially the presolver.)	1.872531	2
	neos-pseudoapplication-4	Jeff Linderoth	(None provided)	1.873534	3
	neos-pseudoapplication-109	Jeff Linderoth	(None provided)	1.884154	4
	supportvectormachine	Toni Sorrell	Suport vector machine with ramp loss. GSVM2-RL is the formulation found in Hess E. and Brooks P. (2015) paper, The Support Vector Machine and Mixed Integer Linear Programming: Ramp Loss SVM with L1-Norm Regularization	1.886402	5

Type:	Instance
Submitter:	Jeff Linderoth
Description:	(None provided)
	MIPLIB Entry

Model Group Assignment from MIPLIB:	neos-pseudoapplication-11
Assigned Model Group Rank/ISS in the MIC:	118 / 2.689

neos-3661949-lesse: Instance-to-Instance Comparison Results

Parent Instance (neos-3661949-lesse)

MIC Top 5 Instances

MIPLIB Top 5 Instances

Instance Summary

neos-3661949-lesse: Instance-to-Model Comparison Results

MIC Top 5 Model Groups

Model Group Summary