bc1: Instance-to-Instance Comparison Results

Type: Instance
Submitter: MIPLIB submission pool
Description: Imported from the MIPLIB2010 submissions.
MIPLIB Entry

Parent Instance (bc1)

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

bc1 Raw bc1 Decomposed bc1 Composite of MIC top 5 bc1 Composite of MIPLIB top 5 bc1 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.
gsvm2rl9 decomposed neos-935234 decomposed mik-250-20-75-5 decomposed gsvm2rl5 decomposed osorio-cta decomposed
Name gsvm2rl9 [MIPLIB] neos-935234 [MIPLIB] mik-250-20-75-5 [MIPLIB] gsvm2rl5 [MIPLIB] osorio-cta [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 / 1.191 2 / 1.305 3 / 1.319 4 / 1.354 5 / 1.401
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIC top 5.
gsvm2rl9 raw neos-935234 raw mik-250-20-75-5 raw gsvm2rl5 raw osorio-cta 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-4954357-bednja decomposed neos-4954340-beaury decomposed neos-4960896-besbre decomposed momentum3 decomposed bc decomposed
Name neos-4954357-bednja [MIPLIB] neos-4954340-beaury [MIPLIB] neos-4960896-besbre [MIPLIB] momentum3 [MIPLIB] neos-4954357-bednja** [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.
426 / 2.015 437 / 2.022 459 / 2.031 823 / 2.331 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-4954357-bednja raw neos-4954340-beaury raw neos-4960896-besbre raw momentum3 raw bc raw

Instance Summary

The table below contains summary information for bc1, the five most similar instances to bc1 according to the MIC, and the five most similar instances to bc1 according to MIPLIB 2017.

INSTANCE SUBMITTER DESCRIPTION ISS RANK
Parent Instance bc1 [MIPLIB] MIPLIB submission pool Imported from the MIPLIB2010 submissions. 0.000000 -
MIC Top 5 gsvm2rl9 [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 1.190779 1
neos-935234 [MIPLIB] NEOS Server Submission Imported from the MIPLIB2010 submissions. 1.304730 2
mik-250-20-75-5 [MIPLIB] MIPLIB submission pool Imported from the MIPLIB2010 submissions. 1.319359 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 1.353649 4
osorio-cta [MIPLIB] Jordi Castro Set of MILP instances of the CTA (Controlled Tabular Adjustment) problem, a method to protect statistical tabular data, belonging to the field of SDC (Statistical Disclosure Control). Raw data of instances are real or pseudo-real, provided by several National Statistical Agencies. We generated the CTA problem for these data. 1.401334 5
MIPLIB Top 5 neos-4954357-bednja [MIPLIB] Jeff Linderoth (None provided) 2.015489 426
neos-4954340-beaury [MIPLIB] Jeff Linderoth (None provided) 2.022415 437
neos-4960896-besbre [MIPLIB] Jeff Linderoth (None provided) 2.031438 459
momentum3 [MIPLIB] T. Koch Snapshot based UMTS planning problem, having a very wide dynamic range in the matrix coefficients and tending to be numerically unstable 2.330994 823
neos-4954357-bednja** [MIPLIB] MIPLIB submission pool Imported from the MIPLIB2010 submissions. N.A.** N.A.**


bc1: Instance-to-Model Comparison Results

Model Group Assignment from MIPLIB: bc
Assigned Model Group Rank/ISS in the MIC: 1 / 0.0

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: bc Model group: mik_250 Model group: neos-pseudoapplication-108 Model group: timtab Model group: supportvectormachine
Name bc mik_250 neos-pseudoapplication-108 timtab 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 / 0.000 2 / 1.467 3 / 1.914 4 / 2.006 5 / 2.022

Model Group Summary

The table below contains summary information for the five most similar model groups to bc1 according to the MIC.

MODEL GROUP SUBMITTER DESCRIPTION ISS RANK
MIC Top 5 bc MIPLIB submission pool Imported from the MIPLIB2010 submissions. 0.000000 1
mik_250 MIPLIB submission pool Imported from the MIPLIB2010 submissions. 1.466766 2
neos-pseudoapplication-108 NEOS Server Submission Model coming from the NEOS Server with unknown application 1.914387 3
timtab C. Liebchen, R. Möhring Public transport scheduling problem 2.005673 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 2.021580 5


** bc could not be decomposed by GCG, and was not included in our dataset.