mcsched: Instance-to-Instance Comparison Results

Type: Instance
Submitter: Q. Chen
Description: Unknown application from COR@L
MIPLIB Entry

Parent Instance (mcsched)

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

mcsched Raw mcsched Decomposed mcsched Composite of MIC top 5 mcsched Composite of MIPLIB top 5 mcsched 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.
scpm1 decomposed gen-ip002 decomposed gen-ip021 decomposed neos-5140963-mincio decomposed k1mushroomi decomposed
Name scpm1 [MIPLIB] gen-ip002 [MIPLIB] gen-ip021 [MIPLIB] neos-5140963-mincio [MIPLIB] k1mushroomi [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 / 1.154 2 / 1.214 3 / 1.229 4 / 1.229 5 / 1.251
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIC top 5.
scpm1 raw gen-ip002 raw gen-ip021 raw neos-5140963-mincio raw k1mushroomi 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.
piperout-08 decomposed gus-sch decomposed piperout-27 decomposed piperout-d20 decomposed piperout-d27 decomposed
Name piperout-08 [MIPLIB] gus-sch [MIPLIB] piperout-27 [MIPLIB] piperout-d20 [MIPLIB] piperout-d27 [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.
231 / 1.527 452 / 1.628 471 / 1.636 796 / 1.977 818 / 2.023
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIPLIB top 5.
piperout-08 raw gus-sch raw piperout-27 raw piperout-d20 raw piperout-d27 raw

Instance Summary

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

INSTANCE SUBMITTER DESCRIPTION ISS RANK
Parent Instance mcsched [MIPLIB] Q. Chen Unknown application from COR@L 0.000000 -
MIC Top 5 scpm1 [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 1.153924 1
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. 1.214364 2
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. 1.228962 3
neos-5140963-mincio [MIPLIB] Jeff Linderoth (None provided) 1.228964 4
k1mushroomi [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 1.251257 5
MIPLIB Top 5 piperout-08 [MIPLIB] Gleb Belov Pipe routing with flexibility constraints. Instances with _GCM in the name are simple routing 1.526768 231
gus-sch [MIPLIB] Alexandra M. Newman course scheduling model 1.627795 452
piperout-27 [MIPLIB] Gleb Belov Pipe routing with flexibility constraints. Instances with _GCM in the name are simple routing 1.636111 471
piperout-d20 [MIPLIB] Gleb Belov Pipe routing with flexibility constraints. Instances with _GCM in the name are simple routing 1.976647 796
piperout-d27 [MIPLIB] Gleb Belov Pipe routing with flexibility constraints. Instances with _GCM in the name are simple routing 2.023362 818


mcsched: 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: pizza Model group: neos-pseudoapplication-109 Model group: k1mushroom Model group: neos-pseudoapplication-74
Name scp pizza neos-pseudoapplication-109 k1mushroom neos-pseudoapplication-74
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 / 1.523 2 / 1.565 3 / 1.591 4 / 1.642 5 / 1.666

Model Group Summary

The table below contains summary information for the five most similar model groups to mcsched 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 1.522571 1
pizza 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 1.564909 2
neos-pseudoapplication-109 Jeff Linderoth (None provided) 1.590768 3
k1mushroom Gleb Belov Linearized Constraint Programming models of the MiniZinc Challenges 2012-2016. I should be able to produce versions with indicator constraints supported by Gurobi and CPLEX, however don't know if you can use them and if there is a standard format. These MPS were produced by Gurobi 7.0.2 using the MiniZinc develop branch on eb536656062ca13325a96b5d0881742c7d0e3c38 1.641662 4
neos-pseudoapplication-74 Jeff Linderoth (None provided) 1.666459 5