railway_8_1_0: Instance-to-Instance Comparison Results

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

Parent Instance (railway_8_1_0)

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

railway_8_1_0 Raw railway_8_1_0 Decomposed railway_8_1_0 Composite of MIC top 5 railway_8_1_0 Composite of MIPLIB top 5 railway_8_1_0 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.
CMS750_4 decomposed berlin_5_8_0 decomposed usAbbrv-8-25_70 decomposed stein45inf decomposed ns2034125 decomposed
Name CMS750_4 [MIPLIB] berlin_5_8_0 [MIPLIB] usAbbrv-8-25_70 [MIPLIB] stein45inf [MIPLIB] ns2034125 [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 / 0.824 2 / 1.010 3 / 1.079 4 / 1.164 5 / 1.206
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIC top 5.
CMS750_4 raw berlin_5_8_0 raw usAbbrv-8-25_70 raw stein45inf raw ns2034125 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.
CMS750_4 decomposed berlin_5_8_0 decomposed usAbbrv-8-25_70 decomposed pigeon-20 decomposed pigeon-16 decomposed
Name CMS750_4 [MIPLIB] berlin_5_8_0 [MIPLIB] usAbbrv-8-25_70 [MIPLIB] pigeon-20 [MIPLIB] pigeon-16 [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 / 0.824 2 / 1.010 3 / 1.079 712 / 1.867 723 / 1.888
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIPLIB top 5.
CMS750_4 raw berlin_5_8_0 raw usAbbrv-8-25_70 raw pigeon-20 raw pigeon-16 raw

Instance Summary

The table below contains summary information for railway_8_1_0, the five most similar instances to railway_8_1_0 according to the MIC, and the five most similar instances to railway_8_1_0 according to MIPLIB 2017.

INSTANCE SUBMITTER DESCRIPTION ISS RANK
Parent Instance railway_8_1_0 [MIPLIB] MIPLIB submission pool Imported from the MIPLIB2010 submissions. 0.000000 -
MIC Top 5 CMS750_4 [MIPLIB] MIPLIB submission pool Imported from the MIPLIB2010 submissions. 0.823864 1
berlin_5_8_0 [MIPLIB] G. Klau Railway optimization problems. The problem was solved using CPLEX 12.3 on a 32 core Sun Galaxy 4600 machine, equipped with eight Quad-Core AMD Opteron 8384 processors at 2.7 GHz and 512 GB RAM. It took approximately 9 hours. The problem was solved using CPLEX 12.4 in about 55 minutes (May 2014). 1.010045 2
usAbbrv-8-25_70 [MIPLIB] publicly available Imported from MIPLIB2010. 1.079413 3
stein45inf [MIPLIB] MIPLIB submission pool Imported from the MIPLIB2010 submissions. 1.164450 4
ns2034125 [MIPLIB] NEOS Server Submission Imported from the MIPLIB2010 submissions. 1.205958 5
MIPLIB Top 5 CMS750_4 [MIPLIB] MIPLIB submission pool Imported from the MIPLIB2010 submissions. 0.823864 1
berlin_5_8_0 [MIPLIB] G. Klau Railway optimization problems. The problem was solved using CPLEX 12.3 on a 32 core Sun Galaxy 4600 machine, equipped with eight Quad-Core AMD Opteron 8384 processors at 2.7 GHz and 512 GB RAM. It took approximately 9 hours. The problem was solved using CPLEX 12.4 in about 55 minutes (May 2014). 1.010045 2
usAbbrv-8-25_70 [MIPLIB] publicly available Imported from MIPLIB2010. 1.079413 3
pigeon-20 [MIPLIB] Sam Allen Instance of 3D packing (container loading) problem 1.867402 712
pigeon-16 [MIPLIB] Sam Allen Instance of 3D packing (container loading) problem 1.887668 723


railway_8_1_0: 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.

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: stein Model group: scp Model group: markshare Model group: neos-pseudoapplication-109 Model group: neos-pseudoapplication-21
Name stein scp markshare neos-pseudoapplication-109 neos-pseudoapplication-21
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 / 1.649 2 / 1.710 3 / 1.778 4 / 1.860 5 / 1.863

Model Group Summary

The table below contains summary information for the five most similar model groups to railway_8_1_0 according to the MIC.

MODEL GROUP SUBMITTER DESCRIPTION ISS RANK
MIC Top 5 stein MIPLIB submission pool Imported from the MIPLIB2010 submissions. 1.648734 1
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 1.710019 2
markshare G. Cornuéjols, M. Dawande Market sharing problem 1.777550 3
neos-pseudoapplication-109 Jeff Linderoth (None provided) 1.859916 4
neos-pseudoapplication-21 NEOS Server Submission Imported from the MIPLIB2010 submissions. 1.862978 5