neos-3230516-zala: Instance-to-Instance Comparison Results

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

Parent Instance (neos-3230516-zala)

All other instances below were be compared against this "query" instance.

neos-3230516-zala Raw neos-3230516-zala Decomposed neos-3230516-zala Composite of MIC top 5 neos-3230516-zala Composite of MIPLIB top 5 neos-3230516-zala Model Group Composite
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.

MIC Top 5 Instances

These are the 5 decomposed CCM images that are most similar to decomposed CCM image for the the query instance, according to the ISS metric.

Decomposed These decomposed images were created by GCG.
neos-3230376-yser decomposed fhnw-binschedule0 decomposed pk1 decomposed gsvm2rl12 decomposed mik-250-20-75-5 decomposed
Name neos-3230376-yser [MIPLIB] fhnw-binschedule0 [MIPLIB] pk1 [MIPLIB] gsvm2rl12 [MIPLIB] mik-250-20-75-5 [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 / 0.713 2 / 0.849 3 / 1.076 4 / 1.083 5 / 1.085
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIC top 5.
neos-3230376-yser raw fhnw-binschedule0 raw pk1 raw gsvm2rl12 raw mik-250-20-75-5 raw

MIPLIB Top 5 Instances

These are the 5 instances that are most closely related to the query instance, according to the instance statistic-based similarity measure employed by MIPLIB 2017

Decomposed These decomposed images were created by GCG.
neos-3230376-yser decomposed genus-g61-25 decomposed neos-3283608-agout decomposed genus-sym-g62-2 decomposed neos-3230511-yuna decomposed
Name neos-3230376-yser [MIPLIB] genus-g61-25 [MIPLIB] neos-3283608-agout [MIPLIB] genus-sym-g62-2 [MIPLIB] neos-3230376-yser** [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 / 0.713 320 / 1.499 391 / 1.555 839 / 2.128 N.A.** / N.A.**
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIPLIB top 5.
neos-3230376-yser raw genus-g61-25 raw neos-3283608-agout raw genus-sym-g62-2 raw neos-3230511-yuna raw

Instance Summary

The table below contains summary information for neos-3230516-zala, the five most similar instances to neos-3230516-zala according to the MIC, and the five most similar instances to neos-3230516-zala according to MIPLIB 2017.

INSTANCE SUBMITTER DESCRIPTION ISS RANK
Parent Instance neos-3230516-zala [MIPLIB] Jeff Linderoth (None provided) 0.000000 -
MIC Top 5 neos-3230376-yser [MIPLIB] Jeff Linderoth (None provided) 0.712567 1
fhnw-binschedule0 [MIPLIB] Simon Felix Scheduling/assignment for an industrial production pipeline 0.848713 2
pk1 [MIPLIB] MIPLIB submission pool Imported from the MIPLIB2010 submissions. 1.075941 3
gsvm2rl12 [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 1.083099 4
mik-250-20-75-5 [MIPLIB] MIPLIB submission pool Imported from the MIPLIB2010 submissions. 1.085387 5
MIPLIB Top 5 neos-3230376-yser [MIPLIB] Jeff Linderoth (None provided) 0.712567 1
genus-g61-25 [MIPLIB] Stephan Beyer Minimum Genus instance of g.61.25 (undirected) of the AT&T Graphs by Stephen C. North. 1.499115 320
neos-3283608-agout [MIPLIB] Jeff Linderoth (None provided) 1.555346 391
genus-sym-g62-2 [MIPLIB] Stephan Beyer Minimum Genus instance, with symmetry breaking constraints, of g.62.2 (undirected) of the AT&T Graphs by Stephen C. North. 2.128264 839
neos-3230376-yser** [MIPLIB] Jeff Linderoth (None provided) N.A.** N.A.**


neos-3230516-zala: Instance-to-Model Comparison Results

Model Group Assignment from MIPLIB: neos-pseudoapplication-4
Assigned Model Group Rank/ISS in the MIC: 1 / 0.808

MIC Top 5 Model Groups

These are the 5 model group composite (MGC) images that are most similar to the decomposed CCM image for the query instance, according to the ISS metric.

These are model group composite (MGC) images for the MIC top 5 model groups.
Model group: neos-pseudoapplication-4 Model group: neos-pseudoapplication-109 Model group: supportvectormachine Model group: scp Model group: neos-pseudoapplication-74
Name neos-pseudoapplication-4 neos-pseudoapplication-109 supportvectormachine scp neos-pseudoapplication-74
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 / 0.808 2 / 1.529 3 / 1.652 4 / 1.683 5 / 1.755

Model Group Summary

The table below contains summary information for the five most similar model groups to neos-3230516-zala according to the MIC.

MODEL GROUP SUBMITTER DESCRIPTION ISS RANK
MIC Top 5 neos-pseudoapplication-4 Jeff Linderoth (None provided) 0.808091 1
neos-pseudoapplication-109 Jeff Linderoth (None provided) 1.529195 2
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 1.651933 3
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 1.682700 4
neos-pseudoapplication-74 Jeff Linderoth (None provided) 1.755292 5


** neos-3230511-yuna could not be decomposed by GCG, and was not included in our dataset.