momentum3: Instance-to-Instance Comparison Results

Type: Instance
Submitter: T. Koch
Description: Snapshot based UMTS planning problem, having a very wide dynamic range in the matrix coefficients and tending to be numerically unstable
MIPLIB Entry

Parent Instance (momentum3)

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

momentum3 Raw momentum3 Decomposed momentum3 Composite of MIC top 5 momentum3 Composite of MIPLIB top 5 momentum3 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.
nh97_potential decomposed binkar10_1 decomposed neos-2294525-abba decomposed neos-1420790 decomposed neos-5266653-tugela decomposed
Name nh97_potential [MIPLIB] binkar10_1 [MIPLIB] neos-2294525-abba [MIPLIB] neos-1420790 [MIPLIB] neos-5266653-tugela [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 / 1.074 2 / 1.173 3 / 1.218 4 / 1.223 5 / 1.236
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIC top 5.
nh97_potential raw binkar10_1 raw neos-2294525-abba raw neos-1420790 raw neos-5266653-tugela 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-4290317-perth decomposed neos-4292145-piako decomposed uccase9 decomposed ran14x18-disj-8 decomposed momentum2 decomposed
Name neos-4290317-perth [MIPLIB] neos-4292145-piako [MIPLIB] uccase9 [MIPLIB] ran14x18-disj-8 [MIPLIB] momentum2 [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.
221 / 1.544 642 / 1.816 722 / 1.915 775 / 1.999 824 / 2.095
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIPLIB top 5.
neos-4290317-perth raw neos-4292145-piako raw uccase9 raw ran14x18-disj-8 raw momentum2 raw

Instance Summary

The table below contains summary information for momentum3, the five most similar instances to momentum3 according to the MIC, and the five most similar instances to momentum3 according to MIPLIB 2017.

INSTANCE SUBMITTER DESCRIPTION ISS RANK
Parent Instance 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 0.000000 -
MIC Top 5 nh97_potential [MIPLIB] MIPLIB submission pool Imported from the MIPLIB2010 submissions. 1.073605 1
binkar10_1 [MIPLIB] H. Mittelmann Relaxed version of problem binkar10 1.172780 2
neos-2294525-abba [MIPLIB] Jeff Linderoth (None provided) 1.218409 3
neos-1420790 [MIPLIB] NEOS Server Submission Imported from the MIPLIB2010 submissions. 1.222905 4
neos-5266653-tugela [MIPLIB] Hans Mittelmann Seem to be VRP output from 2-hour runs of Gurobi on 12 threads is included 1.235612 5
MIPLIB Top 5 neos-4290317-perth [MIPLIB] Jeff Linderoth (None provided) 1.544035 221
neos-4292145-piako [MIPLIB] Jeff Linderoth (None provided) 1.815695 642
uccase9 [MIPLIB] Daniel Espinoza Imported from the MIPLIB2010 submissions. 1.915158 722
ran14x18-disj-8 [MIPLIB] J. Aronson Fixed charge transportation problem 1.999091 775
momentum2 [MIPLIB] T. Koch Snapshot based UMTS planning problem, having a very wide dynamic range in the matrix coefficients and tending to be numerically unstable 2.094564 824


momentum3: Instance-to-Model Comparison Results

Model Group Assignment from MIPLIB: momentum
Assigned Model Group Rank/ISS in the MIC: 127 / 2.645

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: neos-pseudoapplication-90 Model group: neos-pseudoapplication-91 Model group: scp Model group: ustun Model group: fjsp
Name neos-pseudoapplication-90 neos-pseudoapplication-91 scp ustun fjsp
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 / 1.666 2 / 1.734 3 / 1.748 4 / 1.749 5 / 1.754

Model Group Summary

The table below contains summary information for the five most similar model groups to momentum3 according to the MIC.

MODEL GROUP SUBMITTER DESCRIPTION ISS RANK
MIC Top 5 neos-pseudoapplication-90 NEOS Server Submission Model coming from the NEOS Server with unknown application 1.665576 1
neos-pseudoapplication-91 Jeff Linderoth (None provided) 1.734034 2
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 1.747527 3
ustun Berk Ustun MIP to create optimized data-driven scoring systems. See: https://github.com/ustunb/miplib2017-slim#miplib2017-slim for a description. 1.749392 4
fjsp 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 1.753807 5


Updated August 16, 2019