r4l4-02-tree-bounds-50: Instance-to-Instance Comparison Results

Type: Instance
Submitter: Christian Liebchen
Description: Periodic Event Scheduling Problem (PESP) Model for Timetable Optimization in Public Transport Data originating from (see additional file) https://lintim.math.uni-goettingen.de/ and http://num.math.uni-goettingen.de/~m.goerigk/pesplib/ Notation of the variables in the MIP model according to Sec. 9 in Liebchen (2006)
MIPLIB Entry

Parent Instance (r4l4-02-tree-bounds-50)

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

r4l4-02-tree-bounds-50 Raw r4l4-02-tree-bounds-50 Decomposed r4l4-02-tree-bounds-50 Composite of MIC top 5 r4l4-02-tree-bounds-50 Composite of MIPLIB top 5 r4l4-02-tree-bounds-50 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-2991472-kalu decomposed neos-911970 decomposed danoint decomposed timtab1CUTS decomposed pigeon-08 decomposed
Name neos-2991472-kalu [MIPLIB] neos-911970 [MIPLIB] danoint [MIPLIB] timtab1CUTS [MIPLIB] pigeon-08 [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 / 1.112 2 / 1.177 3 / 1.186 4 / 1.189 5 / 1.195
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIC top 5.
neos-2991472-kalu raw neos-911970 raw danoint raw timtab1CUTS raw pigeon-08 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.
bienst1 decomposed bienst2 decomposed newdano decomposed neos-4650160-yukon decomposed uccase12 decomposed
Name bienst1 [MIPLIB] bienst2 [MIPLIB] newdano [MIPLIB] neos-4650160-yukon [MIPLIB] uccase12 [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.
33 / 1.328 35 / 1.331 37 / 1.335 548 / 1.755 920 / 2.364
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIPLIB top 5.
bienst1 raw bienst2 raw newdano raw neos-4650160-yukon raw uccase12 raw

Instance Summary

The table below contains summary information for r4l4-02-tree-bounds-50, the five most similar instances to r4l4-02-tree-bounds-50 according to the MIC, and the five most similar instances to r4l4-02-tree-bounds-50 according to MIPLIB 2017.

INSTANCE SUBMITTER DESCRIPTION ISS RANK
Parent Instance r4l4-02-tree-bounds-50 [MIPLIB] Christian Liebchen Periodic Event Scheduling Problem (PESP) Model for Timetable Optimization in Public Transport Data originating from (see additional file) https://lintim.math.uni-goettingen.de/ and http://num.math.uni-goettingen.de/~m.goerigk/pesplib/ Notation of the variables in the MIP model according to Sec. 9 in Liebchen (2006) 0.000000 -
MIC Top 5 neos-2991472-kalu [MIPLIB] Jeff Linderoth (None provided) 1.112150 1
neos-911970 [MIPLIB] NEOS Server Submission Imported from the MIPLIB2010 submissions. 1.177104 2
danoint [MIPLIB] Daniel Bienstock Telecommunications applications 1.186413 3
timtab1CUTS [MIPLIB] C. Liebchen, R. Möhring Public transport scheduling problem 1.188822 4
pigeon-08 [MIPLIB] Sam Allen Instance of 3D packing (container loading) problem 1.195463 5
MIPLIB Top 5 bienst1 [MIPLIB] MIPLIB submission pool Imported from the MIPLIB2010 submissions. 1.328123 33
bienst2 [MIPLIB] H. Mittelmann Relaxed version of problem bienst 1.330685 35
newdano [MIPLIB] Daniel Bienstock Telecommunications applications 1.335066 37
neos-4650160-yukon [MIPLIB] Jeff Linderoth (None provided) 1.754716 548
uccase12 [MIPLIB] Daniel Espinoza Imported from the MIPLIB2010 submissions. 2.363818 920


r4l4-02-tree-bounds-50: 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: timtab Model group: neos-pseudoapplication-70 Model group: neos-pseudoapplication-40 Model group: pfour Model group: mario
Name timtab neos-pseudoapplication-70 neos-pseudoapplication-40 pfour mario
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 / 1.517 2 / 1.754 3 / 1.791 4 / 1.796 5 / 1.805

Model Group Summary

The table below contains summary information for the five most similar model groups to r4l4-02-tree-bounds-50 according to the MIC.

MODEL GROUP SUBMITTER DESCRIPTION ISS RANK
MIC Top 5 timtab C. Liebchen, R. Möhring Public transport scheduling problem 1.517324 1
neos-pseudoapplication-70 NEOS Server Submission Imported from the MIPLIB2010 submissions. 1.753645 2
neos-pseudoapplication-40 Jeff Linderoth (None provided) 1.791242 3
pfour MIPLIB submission pool Imported from the MIPLIB2010 submissions. 1.795956 4
mario Gleb Belov These are the models from MiniZinc Challenges 2012-2016 (see www.minizinc.org), compiled for MIP WITH INDICATOR CONSTRAINTS using the develop branch of MiniZinc and CPLEX 12.7.1 on 30 April 2017. Thus, these models can only be handled by solvers accepting indicator constraints. For models compiled with big-M/domain decomposition only, see my previous submission to MIPLIB.To recompile, create a directory MODELS, a list lst12_16.txt of the models with full paths to mzn/dzn files of each model per line, and say$> ~/install/libmzn/tests/benchmarking/mzn-test.py -l ../lst12_16.txt -slvPrf MZN-CPLEX -debug 1 -addOption "-timeout 3 -D fIndConstr=true -D fMIPdomains=false" -useJoinedName "-writeModel MODELS_IND/%s.mps" Alternatively, you can compile individual model as follows: $> mzn-cplex -v -s -G linear -output-time ../challenge_2012_2016/mznc2016_probs/zephyrus/zephyrus.mzn ../challenge_2012_2016/mznc2016_p/zephyrus/14__8__6__3.dzn -a -timeout 3 -D fIndConstr=true -D fMIPdomains=false -writeModel MODELS_IND/challenge_2012_2016mznc2016_probszephyruszephyrusmzn-challenge_2012_2016mznc2016_probszephyrus14__8__6__3dzn.mps 1.804861 5