mas74: Instance-to-Instance Comparison Results

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

Parent Instance (mas74)

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

mas74 Raw mas74 Decomposed mas74 Composite of MIC top 5 mas74 Composite of MIPLIB top 5 mas74 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.
mas76 decomposed pb-market-split8-70-4 decomposed gen-ip016 decomposed gen-ip002 decomposed gen-ip021 decomposed
Name mas76 [MIPLIB] pb-market-split8-70-4 [MIPLIB] gen-ip016 [MIPLIB] gen-ip002 [MIPLIB] gen-ip021 [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 / 0.597 2 / 0.692 3 / 0.784 4 / 0.794 5 / 0.806
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIC top 5.
mas76 raw pb-market-split8-70-4 raw gen-ip016 raw gen-ip002 raw gen-ip021 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.
mas76 decomposed ns1456591 decomposed swath decomposed leo2 decomposed leo1 decomposed
Name mas76 [MIPLIB] ns1456591 [MIPLIB] swath [MIPLIB] leo2 [MIPLIB] leo1 [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 / 0.597 371 / 1.541 685 / 1.681 930 / 2.151 932 / 2.155
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIPLIB top 5.
mas76 raw ns1456591 raw swath raw leo2 raw leo1 raw

Instance Summary

The table below contains summary information for mas74, the five most similar instances to mas74 according to the MIC, and the five most similar instances to mas74 according to MIPLIB 2017.

INSTANCE SUBMITTER DESCRIPTION ISS RANK
Parent Instance mas74 [MIPLIB] MIPLIB submission pool Imported from the MIPLIB2010 submissions. 0.000000 -
MIC Top 5 mas76 [MIPLIB] MIPLIB submission pool Imported from the MIPLIB2010 submissions. 0.597495 1
pb-market-split8-70-4 [MIPLIB] Gleb Belov These are the instances 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 instances can only be handled by solvers accepting indicator constraints. For instances 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 instances with full paths to mzn/dzn files of each instance 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 instance 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 0.691509 2
gen-ip016 [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. Solved with XPRESS in a few seconds. 0.783791 3
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. 0.794198 4
gen-ip021 [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. 0.805637 5
MIPLIB Top 5 mas76 [MIPLIB] MIPLIB submission pool Imported from the MIPLIB2010 submissions. 0.597495 1
ns1456591 [MIPLIB] NEOS Server Submission Instance coming from the NEOS Server with unknown application 1.541001 371
swath [MIPLIB] D. Panton Model arising from the defense industry, involves planning missions for radar surveillance. John Forrest and Laszlo Ladanyi solved this instance by reformulation in 1999. Alkis Vazacopoulos reports solving this instance using XPRESS 2006B. 1.680926 685
leo2 [MIPLIB] COR@L test set Instance coming from the COR@L test set with unknown origin 2.151129 930
leo1 [MIPLIB] COR@L test set Instance coming from the COR@L test set with unknown origin 2.154870 932


mas74: 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: scp Model group: markshare Model group: neos-pseudoapplication-21 Model group: stein Model group: enlight
Name scp markshare neos-pseudoapplication-21 stein enlight
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 / 0.658 2 / 0.719 3 / 0.898 4 / 0.938 5 / 1.186

Model Group Summary

The table below contains summary information for the five most similar model groups to mas74 according to the MIC.

MODEL GROUP SUBMITTER DESCRIPTION ISS RANK
MIC Top 5 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 0.657634 1
markshare G. Cornuéjols, M. Dawande Market sharing problem 0.719390 2
neos-pseudoapplication-21 NEOS Server Submission Imported from the MIPLIB2010 submissions. 0.898367 3
stein MIPLIB submission pool Imported from the MIPLIB2010 submissions. 0.938264 4
enlight A. Zymolka Model to solve model of a combinatorial game ``EnLight'' Imported from the MIPLIB2010 submissions. 1.185751 5