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dcmulti: Instance-to-Instance Comparison Results
| Type: | Instance |
| Submitter: | MIPLIB submission pool |
| Description: | Imported from the MIPLIB2010 submissions. |
| MIPLIB Entry |
Parent Instance (dcmulti)
All other instances below were be compared against this "query" instance.  |
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Raw
This is the CCM image before the decomposition procedure has been applied.
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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.
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Composite of MIC Top 5
Composite of the five decomposed CCM images from the MIC Top 5.
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Composite of MIPLIB Top 5
Composite of the five decomposed CCM images from the MIPLIB Top 5.
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Model Group Composite Image
Composite of the decomposed CCM images for every instance in the same model group as this query.
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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.
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| Name | mc8 [MIPLIB] | opt1217 [MIPLIB] | neos-5192052-neckar [MIPLIB] | dws012-01 [MIPLIB] | g200x740 [MIPLIB] | |
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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 instance and all other instances. A smaller ISS value indicates greater similarity.
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1 / 0.724 | 2 / 0.770 | 3 / 0.774 | 4 / 0.785 | 5 / 0.788 | |
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Raw
These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIC top 5.
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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.
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| Name | exp-1-500-5-5 [MIPLIB] | neos-4954672-berkel [MIPLIB] | a1c1s1 [MIPLIB] | dsbmip [MIPLIB] | app3 [MIPLIB] | |
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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 instance and all model groups. A smaller ISS value indicates greater similarity.
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131 / 1.164 | 404 / 1.400 | 413 / 1.410 | 628 / 1.619 | 737 / 1.824 | |
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Raw
These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIPLIB top 5.
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Instance Summary
The table below contains summary information for dcmulti, the five most similar instances to dcmulti according to the MIC, and the five most similar instances to dcmulti according to MIPLIB 2017.
| INSTANCE | SUBMITTER | DESCRIPTION | ISS | RANK | |
|---|---|---|---|---|---|
| Parent Instance | dcmulti [MIPLIB] | MIPLIB submission pool | Imported from the MIPLIB2010 submissions. | 0.000000 | - |
| MIC Top 5 | mc8 [MIPLIB] | F. Ortega, L. Wolsey | Fixed cost network flow problems | 0.724272 | 1 |
| opt1217 [MIPLIB] | MIPLIB submission pool | Imported from the MIPLIB2010 submissions. | 0.770458 | 2 | |
| neos-5192052-neckar [MIPLIB] | Jeff Linderoth | (None provided) | 0.774146 | 3 | |
| dws012-01 [MIPLIB] | Philipp Leise | MILP for designing a decentralized water supply system for drinking water in skyscrapers. The nonlinear characteristics of pumps are integrated with the help of an aggregated convex combination. The instances vary in the total number of floors and load scenarios for water demand. First stage variables represent the layout decisions, second stage variables represent the operational parameters, such as the continuous rotating speed of pumps or binary switching decisions. | 0.785035 | 4 | |
| g200x740 [MIPLIB] | MIPLIB submission pool | Imported from the MIPLIB2010 submissions. | 0.787935 | 5 | |
| MIPLIB Top 5 | exp-1-500-5-5 [MIPLIB] | MIPLIB submission pool | Imported from the MIPLIB2010 submissions. | 1.163560 | 131 |
| neos-4954672-berkel [MIPLIB] | Jeff Linderoth | (None provided) | 1.399938 | 404 | |
| a1c1s1 [MIPLIB] | M. Vyve, Y. Pochet | Lot sizing instance. Alkis Vazacopoulos reports solving this instance using XPRESS 2006B. | 1.410468 | 413 | |
| dsbmip [MIPLIB] | MIPLIB submission pool | Imported from the MIPLIB2010 submissions. | 1.618594 | 628 | |
| app3 [MIPLIB] | Emilie Danna | The archive contains 5 instances coming from 3 applications.app1 is interesting because the continuous variables (w) drive the model.Some solvers have numerical problems on app2 models: some solutions found violate the constraints by a small amount.app2 and app3 models are easy to solve. But they don't solve fast enough for the time limit I have in mind so I'd like to propose them for inclusion in MIPLIB. | 1.823699 | 737 |
dcmulti: 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.
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| Name | neos-pseudoapplication-74 | mc | pizza | pegsolitaire | neos-pseudoapplication-109 | |
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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 instance and all other instances. A smaller ISS value indicates greater similarity.
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1 / 1.113 | 2 / 1.173 | 3 / 1.270 | 4 / 1.471 | 5 / 1.495 |
Model Group Summary
The table below contains summary information for the five most similar model groups to dcmulti according to the MIC.
| MODEL GROUP | SUBMITTER | DESCRIPTION | ISS | RANK | |
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| MIC Top 5 | neos-pseudoapplication-74 | Jeff Linderoth | (None provided) | 1.112879 | 1 |
| mc | F. Ortega, L. Wolsey | Fixed cost network flow problems | 1.173114 | 2 | |
| 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 | 1.270223 | 3 | |
| pegsolitaire | Hiroshige Dan | Model to solve model of a board game "Peg solitaire" | 1.470997 | 4 | |
| neos-pseudoapplication-109 | Jeff Linderoth | (None provided) | 1.495156 | 5 |
