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k1mushroom
| Type: | Model Group |
| Submitter: | Gleb Belov |
| Description: | 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 |
Parent Model Group (k1mushroom)
All other model groups below were be compared against this "query" model group.  |
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Model Group Composite (MGC) image
Composite of the decomposed CCM images for every instance in the query model group.
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Component Instances (Decomposed)
These are the decomposed CCM images for each instance in the query model group. |
These are component instance images.
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| Name | k1mushroomi | k1mushroom |
MIC Top 5 Model Groups
These are the 5 MGC images that are most similar to the MGC image for the query model group, according to the ISS metric. |
FIXME - These are model group composite images.
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| Name | splice | pizza | pegsolitaire | scp | neos-pseudoapplication-74 | |
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Rank / ISS
The image-based structural similarity (ISS) metric measures the Euclidean distance between the image-based feature vectors for the query model group and all other model groups. A smaller ISS value indicates greater similarity.
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1 / 1.069 | 2 / 1.496 | 3 / 1.558 | 4 / 1.587 | 5 / 1.633 |
Model Group Summary
The table below contains summary information for k1mushroom, and for the five most similar model groups to k1mushroom according to the MIC.
| MODEL GROUP | SUBMITTER | DESCRIPTION | ISS | RANK | |
|---|---|---|---|---|---|
| Parent Model Group | 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 | 0.000000 | - |
| MIC Top 5 | splice | 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 | 1.068679 | 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 | 1.495926 | 2 | |
| pegsolitaire | Hiroshige Dan | Model to solve model of a board game "Peg solitaire" | 1.558388 | 3 | |
| 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 | 1.587000 | 4 | |
| neos-pseudoapplication-74 | Jeff Linderoth | (None provided) | 1.633281 | 5 |
