ns1679495: Instance-to-Instance Comparison Results

Type: Instance
Submitter: NEOS Server Submission
Description: Instance coming from the NEOS Server with unknown application.
MIPLIB Entry

Parent Instance (ns1679495)

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

ns1679495 Raw ns1679495 Decomposed ns1679495 Composite of MIC top 5 ns1679495 Composite of MIPLIB top 5 ns1679495 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-633273 decomposed enlight4 decomposed flugplinf decomposed stein15inf decomposed stein9inf decomposed
Name neos-633273 [MIPLIB] enlight4 [MIPLIB] flugplinf [MIPLIB] stein15inf [MIPLIB] stein9inf [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 / 0.891 2 / 0.925 3 / 0.928 4 / 0.932 5 / 0.938
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIC top 5.
neos-633273 raw enlight4 raw flugplinf raw stein15inf raw stein9inf 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.
zeil decomposed neos-1420790 decomposed neos-4954357-bednja decomposed neos-4954340-beaury decomposed neos-1420546 decomposed
Name zeil [MIPLIB] neos-1420790 [MIPLIB] neos-4954357-bednja [MIPLIB] neos-4954340-beaury [MIPLIB] neos-1420546 [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.
250 / 1.354 482 / 1.547 615 / 1.688 651 / 1.737 695 / 1.830
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIPLIB top 5.
zeil raw neos-1420790 raw neos-4954357-bednja raw neos-4954340-beaury raw neos-1420546 raw

Instance Summary

The table below contains summary information for ns1679495, the five most similar instances to ns1679495 according to the MIC, and the five most similar instances to ns1679495 according to MIPLIB 2017.

INSTANCE SUBMITTER DESCRIPTION ISS RANK
Parent Instance ns1679495 [MIPLIB] NEOS Server Submission Instance coming from the NEOS Server with unknown application. 0.000000 -
MIC Top 5 neos-633273 [MIPLIB] NEOS Server Submission Collection of anonymous submissions to the NEOS Server for Optimization 0.891153 1
enlight4 [MIPLIB] A. Zymolka Model to solve instance of a combinatorial game ``EnLight'' Imported from the MIPLIB2010 submissions. 0.924534 2
flugplinf [MIPLIB] MIPLIB submission pool Imported from the MIPLIB2010 submissions. 0.927719 3
stein15inf [MIPLIB] MIPLIB submission pool Imported from the MIPLIB2010 submissions. 0.932045 4
stein9inf [MIPLIB] MIPLIB submission pool Imported from the MIPLIB2010 submissions. 0.938098 5
MIPLIB Top 5 zeil [MIPLIB] Andreas Bärmann A model that computes an optimal adaptation of a given timetable draft for a small portion of the German railway network. The aim is to shift the planned departure times of the trains slightly, such that the maximum power consumption (averaed over 15-minute intervalls of the planning horizon) is as small as possible. 1.353955 250
neos-1420790 [MIPLIB] NEOS Server Submission Imported from the MIPLIB2010 submissions. 1.547427 482
neos-4954357-bednja [MIPLIB] Jeff Linderoth (None provided) 1.687636 615
neos-4954340-beaury [MIPLIB] Jeff Linderoth (None provided) 1.736837 651
neos-1420546 [MIPLIB] NEOS Server Submission Imported from the MIPLIB2010 submissions. 1.830352 695


ns1679495: Instance-to-Model Comparison Results

Model Group Assignment from MIPLIB: neos-pseudoapplication-9
Assigned Model Group Rank/ISS in the MIC: 93 / 2.611

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: neos-pseudoapplication-109 Model group: neos-pseudoapplication-74 Model group: scp Model group: proteindesign Model group: supportvectormachine
Name neos-pseudoapplication-109 neos-pseudoapplication-74 scp proteindesign supportvectormachine
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 / 1.593 2 / 1.677 3 / 1.681 4 / 1.717 5 / 1.730

Model Group Summary

The table below contains summary information for the five most similar model groups to ns1679495 according to the MIC.

MODEL GROUP SUBMITTER DESCRIPTION ISS RANK
MIC Top 5 neos-pseudoapplication-109 Jeff Linderoth (None provided) 1.593212 1
neos-pseudoapplication-74 Jeff Linderoth (None provided) 1.677161 2
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 1.680876 3
proteindesign 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 1.716983 4
supportvectormachine Toni Sorrell Suport vector machine with ramp loss. GSVM2-RL is the formulation found in Hess E. and Brooks P. (2015) paper, The Support Vector Machine and Mixed Integer Linear Programming: Ramp Loss SVM with L1-Norm Regularization 1.730491 5


Updated August 16, 2019