pb-fit2d: Instance-to-Instance Comparison Results

Type: Instance
Submitter: Gleb Belov
Description: 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
MIPLIB Entry

Parent Instance (pb-fit2d)

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

pb-fit2d Raw pb-fit2d Decomposed pb-fit2d Composite of MIC top 5 pb-fit2d Composite of MIPLIB top 5 pb-fit2d 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.
neos-4703857-ahuroa decomposed polygonpack5-15 decomposed graph40-80-1rand decomposed neos-4322846-ryton decomposed graph40-40-1rand decomposed
Name neos-4703857-ahuroa [MIPLIB] polygonpack5-15 [MIPLIB] graph40-80-1rand [MIPLIB] neos-4322846-ryton [MIPLIB] graph40-40-1rand [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.
1 / 0.615 2 / 0.631 3 / 0.633 4 / 0.635 5 / 0.636
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIC top 5.
neos-4703857-ahuroa raw polygonpack5-15 raw graph40-80-1rand raw neos-4322846-ryton raw graph40-40-1rand 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-787933 decomposed peg-solitaire-a3 decomposed neos-2328163-agri decomposed neos-4355351-swalm decomposed co-100 decomposed
Name neos-787933 [MIPLIB] peg-solitaire-a3 [MIPLIB] neos-2328163-agri [MIPLIB] neos-4355351-swalm [MIPLIB] co-100 [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.
379 / 1.299 411 / 1.326 585 / 1.551 885 / 2.413 982 / 3.842
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIPLIB top 5.
neos-787933 raw peg-solitaire-a3 raw neos-2328163-agri raw neos-4355351-swalm raw co-100 raw

Instance Summary

The table below contains summary information for pb-fit2d, the five most similar instances to pb-fit2d according to the MIC, and the five most similar instances to pb-fit2d according to MIPLIB 2017.

INSTANCE SUBMITTER DESCRIPTION ISS RANK
Parent Instance pb-fit2d [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 0.000000 -
MIC Top 5 neos-4703857-ahuroa [MIPLIB] Jeff Linderoth (None provided) 0.614925 1
polygonpack5-15 [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. 0.630655 2
graph40-80-1rand [MIPLIB] Michael Bastubbe Packing Cuts in Undirected Graphs. Instances are described in 4.1. 0.632831 3
neos-4322846-ryton [MIPLIB] Jeff Linderoth (None provided) 0.635267 4
graph40-40-1rand [MIPLIB] Michael Bastubbe Packing Cuts in Undirected Graphs. Instances are described in 4.1. 0.635986 5
MIPLIB Top 5 neos-787933 [MIPLIB] NEOS Server Submission Imported from the MIPLIB2010 submissions. 1.298604 379
peg-solitaire-a3 [MIPLIB] Hiroshige Dan Model to solve instance of a board game "Peg solitaire" 1.325921 411
neos-2328163-agri [MIPLIB] Jeff Linderoth (None provided) 1.551297 585
neos-4355351-swalm [MIPLIB] Jeff Linderoth (None provided) 2.413434 885
co-100 [MIPLIB] Axel Werner Model from optical access network planning 3.841782 982


pb-fit2d: Instance-to-Model Comparison Results

Model Group Assignment from MIPLIB: pb-
Assigned Model Group Rank/ISS in the MIC: 141 / 2.905

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: map Model group: rmatr Model group: neos-pseudoapplication-2 Model group: sp_product Model group: polygonpack
Name map rmatr neos-pseudoapplication-2 sp_product polygonpack
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 / 0.767 2 / 0.873 3 / 0.946 4 / 0.963 5 / 0.990

Model Group Summary

The table below contains summary information for the five most similar model groups to pb-fit2d according to the MIC.

MODEL GROUP SUBMITTER DESCRIPTION ISS RANK
MIC Top 5 map Kiyan Ahmadizadeh Land parcel selection problems motivated by Red-Cockaded Woodpecker conservation problem 0.767253 1
rmatr Dmitry Krushinsky Model coming from a formulation of the p-Median problem using square cost matrices 0.873370 2
neos-pseudoapplication-2 NEOS Server Submission Imported from the MIPLIB2010 submissions. 0.946488 3
sp_product MIPLIB submission pool Imported from the MIPLIB2010 submissions. 0.963035 4
polygonpack 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. Model 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. 0.990420 5


Updated August 16, 2019