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comp16-3idx: Instance-to-Instance Comparison Results
Type: | Instance |
Submitter: | Matias Sørensen |
Description: | Instances comp01-21 of curriculum based course timetabling from the International Timetabling Competition 2007. These are the full models using three-index decision variables. |
MIPLIB Entry |
Parent Instance (comp16-3idx)
All other instances below were be compared against this "query" instance.
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 | neos-631710 [MIPLIB] | ns1849932 [MIPLIB] | polygonpack4-10 [MIPLIB] | graph20-80-1rand [MIPLIB] | graph40-20-1rand [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.
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1 / 0.906 | 2 / 0.982 | 3 / 1.018 | 4 / 1.028 | 5 / 1.033 | |
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 | ns1631475 [MIPLIB] | mkc1 [MIPLIB] | piperout-08 [MIPLIB] | neos-4391920-timok [MIPLIB] | piperout-27 [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.
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263 / 1.314 | 281 / 1.343 | 362 / 1.436 | 443 / 1.501 | 555 / 1.589 | |
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 comp16-3idx, the five most similar instances to comp16-3idx according to the MIC, and the five most similar instances to comp16-3idx according to MIPLIB 2017.
INSTANCE | SUBMITTER | DESCRIPTION | ISS | RANK | |
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Parent Instance | comp16-3idx [MIPLIB] | Matias Sørensen | Instances comp01-21 of curriculum based course timetabling from the International Timetabling Competition 2007. These are the full models using three-index decision variables. | 0.000000 | - |
MIC Top 5 | neos-631710 [MIPLIB] | NEOS Server Submission | Instance coming from the NEOS Server with unknown application. Solved with Gurobi 4.6.1 (12 threads) in 1264.7 sec. | 0.905601 | 1 |
ns1849932 [MIPLIB] | NEOS Server Submission | Instance coming from the NEOS Server with unknown application. | 0.981747 | 2 | |
polygonpack4-10 [MIPLIB] | Antonio Frangioni | Given a set P of polygons, not necessarily convex, and a rectangle, we want to find the subset S of P with largest possible total area and a position every p in S so that there are no overlaps and they are all included in the rectangle. We allow a small set of rotations (0, 90, 180, 270 degrees) for every polygon. The problem is simplified w.r.t. the real application because the polygons do not have (fully encircled) "holes", which are supposedly filled-in separately, although they can have "bays". Models are saved as .lp. Instance LpPackingModel_Dim means that we are trying to pack polygons taken from set ; there are currently 5 different sets, and is 7, 10 or 15. | 1.017912 | 3 | |
graph20-80-1rand [MIPLIB] | Michael Bastubbe | Packing Cuts in Undirected Graphs. Instances are described in 4.1. | 1.027759 | 4 | |
graph40-20-1rand [MIPLIB] | Michael Bastubbe | Packing Cuts in Undirected Graphs. Instances are described in 4.1. | 1.033275 | 5 | |
MIPLIB Top 5 | ns1631475 [MIPLIB] | NEOS Server Submission | Traveling salesman problem model | 1.313747 | 263 |
mkc1 [MIPLIB] | MIPLIB submission pool | Imported from the MIPLIB2010 submissions. | 1.342774 | 281 | |
piperout-08 [MIPLIB] | Gleb Belov | Pipe routing with flexibility constraints. Instances with _GCM in the name are simple routing | 1.435803 | 362 | |
neos-4391920-timok [MIPLIB] | Jeff Linderoth | (None provided) | 1.500887 | 443 | |
piperout-27 [MIPLIB] | Gleb Belov | Pipe routing with flexibility constraints. Instances with _GCM in the name are simple routing | 1.589479 | 555 |
comp16-3idx: Instance-to-Model Comparison Results
Model Group Assignment from MIPLIB: | coursetimetabling |
Assigned Model Group Rank/ISS in the MIC: | 132 / 2.706 |
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 | mapping | n37 | graphs | sp_product | seqsolve | |
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 / 1.248 | 2 / 1.406 | 3 / 1.419 | 4 / 1.420 | 5 / 1.428 |
Model Group Summary
The table below contains summary information for the five most similar model groups to comp16-3idx according to the MIC.
MODEL GROUP | SUBMITTER | DESCRIPTION | ISS | RANK | |
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MIC Top 5 | mapping | 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 | 1.247636 | 1 |
n37 | J. Aronson | Fixed charge transportation problem | 1.406417 | 2 | |
graphs | Michael Bastubbe | Packing Cuts in Undirected Graphs. Models are described in 4.1. | 1.419385 | 3 | |
sp_product | MIPLIB submission pool | Imported from the MIPLIB2010 submissions. | 1.420096 | 4 | |
seqsolve | Irv Lustig | The 3 problems in this group (seqsolve1-seqsolve3) represent a hierarchical optimization process, which is derived from a customer problem for assigning people to sites into blocks of time on days of the week. The specialty of this submission is that the best known solution for seqsolveX can be used as a MIP start for seqsolveX+1. For a description of the connections between the problems, please refer to the README.txt contained in the model data for this submission, which also includes MIP start files and a Gurobi log file. | 1.427542 | 5 |