tpl-tub-ws1617: Instance-to-Instance Comparison Results

Type: Instance
Submitter: János Höner
Description: Model for the Post-Enrollment Course Timetabling Problem at TU Berlin from the summer term 2016 and the winter term 2016/2017
MIPLIB Entry

Parent Instance (tpl-tub-ws1617)

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

tpl-tub-ws1617 Raw tpl-tub-ws1617 Decomposed tpl-tub-ws1617 Composite of MIC top 5 tpl-tub-ws1617 Composite of MIPLIB top 5 tpl-tub-ws1617 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.
tpl-tub-ss16 decomposed scpl4 decomposed gen-ip036 decomposed f2gap401600 decomposed ns1952667 decomposed
Name tpl-tub-ss16 [MIPLIB] scpl4 [MIPLIB] gen-ip036 [MIPLIB] f2gap401600 [MIPLIB] ns1952667 [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 / 0.493 2 / 1.075 3 / 1.201 4 / 1.203 5 / 1.219
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIC top 5.
tpl-tub-ss16 raw scpl4 raw gen-ip036 raw f2gap401600 raw ns1952667 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.
tpl-tub-ss16 decomposed rwth-timetable decomposed neos-850681 decomposed nb10tb decomposed supportcase31 decomposed
Name tpl-tub-ss16 [MIPLIB] rwth-timetable [MIPLIB] neos-850681 [MIPLIB] nb10tb [MIPLIB] supportcase31 [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 / 0.493 14 / 1.276 64 / 1.610 372 / 1.984 753 / 2.140
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIPLIB top 5.
tpl-tub-ss16 raw rwth-timetable raw neos-850681 raw nb10tb raw supportcase31 raw

Instance Summary

The table below contains summary information for tpl-tub-ws1617, the five most similar instances to tpl-tub-ws1617 according to the MIC, and the five most similar instances to tpl-tub-ws1617 according to MIPLIB 2017.

INSTANCE SUBMITTER DESCRIPTION ISS RANK
Parent Instance tpl-tub-ws1617 [MIPLIB] János Höner Model for the Post-Enrollment Course Timetabling Problem at TU Berlin from the summer term 2016 and the winter term 2016/2017 0.000000 -
MIC Top 5 tpl-tub-ss16 [MIPLIB] János Höner Model for the Post-Enrollment Course Timetabling Problem at TU Berlin from the summer term 2016 and the winter term 2016/2017 0.493365 1
scpl4 [MIPLIB] Shunji Umetani This is a random test instance 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 instances. We have also generated reduced instances 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 instance generator program from the following web site. https://sites.google.com/site/shunjiumetani/benchmark 1.075205 2
gen-ip036 [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. 1.200832 3
f2gap401600 [MIPLIB] Salim Haddadi Restrictions of well-known hard generalized assignment problem instances (D10400,D20400,D40400,D15900,D30900,D60900,D201600,D401600,D801600) 1.203194 4
ns1952667 [MIPLIB] NEOS Server Submission Instance coming from the NEOS Server with unknown application 1.218507 5
MIPLIB Top 5 tpl-tub-ss16 [MIPLIB] János Höner Model for the Post-Enrollment Course Timetabling Problem at TU Berlin from the summer term 2016 and the winter term 2016/2017 0.493365 1
rwth-timetable [MIPLIB] Gerald Lach University Course Timetabling from the RWTH Aachen 1.276094 14
neos-850681 [MIPLIB] NEOS Server Submission Imported from the MIPLIB2010 submissions. 1.610408 64
nb10tb [MIPLIB] Serge Bisaillon Forestry industry model 1.983757 372
supportcase31 [MIPLIB] Domenico Salvagnin Instance coming from IBM developerWorks forum with unknown application. 2.140447 753


tpl-tub-ws1617: 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: independentset Model group: generated Model group: neos-pseudoapplication-21 Model group: neos-pseudoapplication-101 Model group: scp
Name independentset generated neos-pseudoapplication-21 neos-pseudoapplication-101 scp
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 / 1.138 2 / 1.256 3 / 1.268 4 / 1.277 5 / 1.311

Model Group Summary

The table below contains summary information for the five most similar model groups to tpl-tub-ws1617 according to the MIC.

MODEL GROUP SUBMITTER DESCRIPTION ISS RANK
MIC Top 5 independentset Toni Sorrell These models are based on Neil Sloane's Challenge problems: Independent Sets in Graphs. 1.138116 1
generated Simon Bowly Randomly generated integer and binary programming models. These results are part of an early phase of work aimed at generating diverse and challenging MIP models for experimental testing. We have aimed to produce small integer and binary programming models which are reasonably difficult to solve and have varied structure, eliciting a range of behaviour in state of the art algorithms. 1.256340 2
neos-pseudoapplication-21 NEOS Server Submission Imported from the MIPLIB2010 submissions. 1.268143 3
neos-pseudoapplication-101 NEOS Server Submission Model coming from the NEOS Server with unknown application. Infeasibility claimed by CPLEX 12.6 and CPLEX 12.6.1 with extreme numerical caution emphasi after 4 and 2 hours computation, respectively. 1.276806 4
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 1.311420 5