tokyometro: Instance-to-Instance Comparison Results

Type: Instance
Submitter: Hsiang-Yun WU
Description: The layout model for Tokyo Metro Map
MIPLIB Entry

Parent Instance (tokyometro)

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

tokyometro Raw tokyometro Decomposed tokyometro Composite of MIC top 5 tokyometro Composite of MIPLIB top 5 tokyometro 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.
gen-ip054 decomposed timtab1 decomposed f2gap40400 decomposed markshare2 decomposed gen-ip002 decomposed
Name gen-ip054 [MIPLIB] timtab1 [MIPLIB] f2gap40400 [MIPLIB] markshare2 [MIPLIB] gen-ip002 [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 / 1.209 2 / 1.263 3 / 1.275 4 / 1.278 5 / 1.279
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIC top 5.
gen-ip054 raw timtab1 raw f2gap40400 raw markshare2 raw gen-ip002 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.
lectsched-4-obj decomposed allcolor10 decomposed allcolor58 decomposed lectsched-5-obj decomposed neos-4165869-wannon decomposed
Name lectsched-4-obj [MIPLIB] allcolor10 [MIPLIB] allcolor58 [MIPLIB] lectsched-5-obj [MIPLIB] neos-4165869-wannon [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.
157 / 1.540 183 / 1.552 208 / 1.562 524 / 1.725 725 / 1.912
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIPLIB top 5.
lectsched-4-obj raw allcolor10 raw allcolor58 raw lectsched-5-obj raw neos-4165869-wannon raw

Instance Summary

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

INSTANCE SUBMITTER DESCRIPTION ISS RANK
Parent Instance tokyometro [MIPLIB] Hsiang-Yun WU The layout model for Tokyo Metro Map 0.000000 -
MIC Top 5 gen-ip054 [MIPLIB] Simon Bowly Randomly generated integer and binary programming instances. These results are part of an early phase of work aimed at generating diverse and challenging MIP instances for experimental testing. We have aimed to produce small integer and binary programming instances which are reasonably difficult to solve and have varied structure, eliciting a range of behaviour in state of the art algorithms. 1.208716 1
timtab1 [MIPLIB] C. Liebchen, R. Möhring Public transport scheduling problem 1.263168 2
f2gap40400 [MIPLIB] Salim Haddadi Restrictions of well-known hard generalized assignment problem instances (D10400,D20400,D40400,D15900,D30900,D60900,D201600,D401600,D801600) 1.274545 3
markshare2 [MIPLIB] G. Cornuéjols, M. Dawande Market sharing problem 1.277672 4
gen-ip002 [MIPLIB] Simon Bowly Randomly generated integer and binary programming instances. These results are part of an early phase of work aimed at generating diverse and challenging MIP instances for experimental testing. We have aimed to produce small integer and binary programming instances which are reasonably difficult to solve and have varied structure, eliciting a range of behaviour in state of the art algorithms. 1.279426 5
MIPLIB Top 5 lectsched-4-obj [MIPLIB] Harald Schilly University lecture scheduling instance 1.539871 157
allcolor10 [MIPLIB] Domenico Salvagnin Prepack optimization instance. 1.552135 183
allcolor58 [MIPLIB] Domenico Salvagnin Prepack optimization model. 1.561627 208
lectsched-5-obj [MIPLIB] Harald Schilly scheduling lectures at university - smaller subset of data with objective to minimize certain overlappings 1.725014 524
neos-4165869-wannon [MIPLIB] Hans Mittelmann Collection of anonymous submissions to the NEOS Server for Optimization 1.911848 725


tokyometro: 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: markshare Model group: scp Model group: stein Model group: neos-pseudoapplication-21 Model group: timtab
Name markshare scp stein neos-pseudoapplication-21 timtab
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 / 1.533 2 / 1.542 3 / 1.606 4 / 1.726 5 / 1.743

Model Group Summary

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

MODEL GROUP SUBMITTER DESCRIPTION ISS RANK
MIC Top 5 markshare G. Cornuéjols, M. Dawande Market sharing problem 1.533402 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 1.542146 2
stein MIPLIB submission pool Imported from the MIPLIB2010 submissions. 1.606259 3
neos-pseudoapplication-21 NEOS Server Submission Imported from the MIPLIB2010 submissions. 1.726327 4
timtab C. Liebchen, R. Möhring Public transport scheduling problem 1.743248 5


Updated August 16, 2019