peg-solitaire-a3: Instance-to-Instance Comparison Results

Type: Instance
Submitter: Hiroshige Dan
Description: Model to solve instance of a board game "Peg solitaire"
MIPLIB Entry

Parent Instance (peg-solitaire-a3)

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

peg-solitaire-a3 Raw peg-solitaire-a3 Decomposed peg-solitaire-a3 Composite of MIC top 5 peg-solitaire-a3 Composite of MIPLIB top 5 peg-solitaire-a3 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.
k1mushroomi decomposed neos-827015 decomposed splice1k1i decomposed app1-1 decomposed app1-2 decomposed
Name k1mushroomi [MIPLIB] neos-827015 [MIPLIB] splice1k1i [MIPLIB] app1-1 [MIPLIB] app1-2 [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 / 0.594 2 / 0.634 3 / 0.636 4 / 0.696 5 / 0.712
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIC top 5.
k1mushroomi raw neos-827015 raw splice1k1i raw app1-1 raw app1-2 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.
neos-2328163-agri decomposed neos-4343293-stony decomposed neos-3237086-abava decomposed neos-4333464-siret decomposed neos-4355351-swalm decomposed
Name neos-2328163-agri [MIPLIB] neos-4343293-stony [MIPLIB] neos-3237086-abava [MIPLIB] neos-4333464-siret [MIPLIB] neos-4355351-swalm [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.
196 / 1.410 625 / 1.719 708 / 1.831 859 / 2.238 902 / 2.498
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIPLIB top 5.
neos-2328163-agri raw neos-4343293-stony raw neos-3237086-abava raw neos-4333464-siret raw neos-4355351-swalm raw

Instance Summary

The table below contains summary information for peg-solitaire-a3, the five most similar instances to peg-solitaire-a3 according to the MIC, and the five most similar instances to peg-solitaire-a3 according to MIPLIB 2017.

INSTANCE SUBMITTER DESCRIPTION ISS RANK
Parent Instance peg-solitaire-a3 [MIPLIB] Hiroshige Dan Model to solve instance of a board game "Peg solitaire" 0.000000 -
MIC Top 5 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: $> mzn-cplex -v -s -G linear -output-time ../challenge_2012_2016/mznc2016_probs/zephyrus/zephyrus.mzn ../challenge_2012_2016/mznc2016_p/zephyrus/14__8__6__3.dzn -a -timeout 3 -D fIndConstr=true -D fMIPdomains=false -writeModel MODELS_IND/challenge_2012_2016mznc2016_probszephyruszephyrusmzn-challenge_2012_2016mznc2016_probszephyrus14__8__6__3dzn.mps 0.594499 1
neos-827015 [MIPLIB] NEOS Server Submission Imported from the MIPLIB2010 submissions. 0.633544 2
splice1k1i [MIPLIB] Gleb Belov These are the instances from MiniZinc Challenges 2012-2016 (see www.minizinc.org), compiled for MIP WITH INDICATOR CONSTRAINTS using the develop branch of MiniZinc and CPLEX 12.7.1 on 30 April 2017. Thus, these instances can only be handled by solvers accepting indicator constraints. For instances compiled with big-M/domain decomposition only, see my previous submission to MIPLIB.To recompile, create a directory MODELS, a list lst12_16.txt of the instances with full paths to mzn/dzn files of each instance per line, and say$> ~/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 0.635733 3
app1-1 [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. 0.695886 4
app1-2 [MIPLIB] Emilie Danna Undisclosed industrial application from Google 0.712315 5
MIPLIB Top 5 neos-2328163-agri [MIPLIB] Jeff Linderoth (None provided) 1.410385 196
neos-4343293-stony [MIPLIB] Jeff Linderoth (None provided) 1.718761 625
neos-3237086-abava [MIPLIB] Jeff Linderoth (None provided) 1.830977 708
neos-4333464-siret [MIPLIB] Jeff Linderoth (None provided) 2.238047 859
neos-4355351-swalm [MIPLIB] Jeff Linderoth (None provided) 2.497711 902


peg-solitaire-a3: Instance-to-Model Comparison Results

Model Group Assignment from MIPLIB: pegsolitaire
Assigned Model Group Rank/ISS in the MIC: 1 / 0.0

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: pegsolitaire Model group: pizza Model group: neos-pseudoapplication-74 Model group: k1mushroom Model group: splice
Name pegsolitaire pizza neos-pseudoapplication-74 k1mushroom splice
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 / 0.000 2 / 1.196 3 / 1.514 4 / 1.558 5 / 1.583

Model Group Summary

The table below contains summary information for the five most similar model groups to peg-solitaire-a3 according to the MIC.

MODEL GROUP SUBMITTER DESCRIPTION ISS RANK
MIC Top 5 pegsolitaire Hiroshige Dan Model to solve model of a board game "Peg solitaire" 0.000000 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 1.195545 2
neos-pseudoapplication-74 Jeff Linderoth (None provided) 1.513560 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 1.558388 4
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 1.583399 5