sing17: Instance-to-Instance Comparison Results

Type: Instance
Submitter: Daniel Espinoza
Description: Imported from the MIPLIB2010 submissions.
MIPLIB Entry

Parent Instance (sing17)

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

sing17 Raw sing17 Decomposed sing17 Composite of MIC top 5 sing17 Composite of MIPLIB top 5 sing17 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.
sing5 decomposed sing11 decomposed neos-941313 decomposed sing44 decomposed cvs16r89-60 decomposed
Name sing5 [MIPLIB] sing11 [MIPLIB] neos-941313 [MIPLIB] sing44 [MIPLIB] cvs16r89-60 [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 / 0.357 2 / 0.377 3 / 0.414 4 / 0.430 5 / 0.430
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIC top 5.
sing5 raw sing11 raw neos-941313 raw sing44 raw cvs16r89-60 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.
sing5 decomposed sing11 decomposed neos-780889 decomposed satellites2-60-fs decomposed satellites4-25 decomposed
Name sing5 [MIPLIB] sing11 [MIPLIB] neos-780889 [MIPLIB] satellites2-60-fs [MIPLIB] satellites4-25 [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.
1 / 0.357 2 / 0.377 105 / 0.779 613 / 1.680 893 / 2.503
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIPLIB top 5.
sing5 raw sing11 raw neos-780889 raw satellites2-60-fs raw satellites4-25 raw

Instance Summary

The table below contains summary information for sing17, the five most similar instances to sing17 according to the MIC, and the five most similar instances to sing17 according to MIPLIB 2017.

INSTANCE SUBMITTER DESCRIPTION ISS RANK
Parent Instance sing17 [MIPLIB] Daniel Espinoza Imported from the MIPLIB2010 submissions. 0.000000 -
MIC Top 5 sing5 [MIPLIB] Daniel Espinoza Imported from the MIPLIB2010 submissions. 0.356910 1
sing11 [MIPLIB] Daniel Espinoza Imported from the MIPLIB2010 submissions. 0.376626 2
neos-941313 [MIPLIB] NEOS Server Submission Instance coming from the NEOS Server with unknown application 0.413823 3
sing44 [MIPLIB] Daniel Espinoza Imported from the MIPLIB2010 submissions. 0.429623 4
cvs16r89-60 [MIPLIB] Michael Bastubbe Capacitated vertex separator problem on randomly generated hypergraph with 89 vertices and 60 hyperedges in at most 16 components each including at most 6 vertices. 0.430374 5
MIPLIB Top 5 sing5 [MIPLIB] Daniel Espinoza Imported from the MIPLIB2010 submissions. 0.356910 1
sing11 [MIPLIB] Daniel Espinoza Imported from the MIPLIB2010 submissions. 0.376626 2
neos-780889 [MIPLIB] NEOS Server Submission Imported from the MIPLIB2010 submissions. 0.778620 105
satellites2-60-fs [MIPLIB] He Renjie Satellite scheduling instance 1.680400 613
satellites4-25 [MIPLIB] He Renjie Ihe attachment is some instances generated from real life satelliteschedule problem data,these instances are easier comparable to real lifeproblem. The work is done by me and Alberto Ceselli from Univeristy ofMilano. I donnot know it is hard enough or not, if needs , I can generatemore difficult instances. 2.503155 893


sing17: Instance-to-Model Comparison Results

Model Group Assignment from MIPLIB: sing
Assigned Model Group Rank/ISS in the MIC: 9 / 0.773

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: sp_product Model group: map Model group: n37 Model group: allcolor Model group: rmatr
Name sp_product map n37 allcolor rmatr
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 / 0.641 2 / 0.664 3 / 0.677 4 / 0.692 5 / 0.752

Model Group Summary

The table below contains summary information for the five most similar model groups to sing17 according to the MIC.

MODEL GROUP SUBMITTER DESCRIPTION ISS RANK
MIC Top 5 sp_product MIPLIB submission pool Imported from the MIPLIB2010 submissions. 0.640885 1
map Kiyan Ahmadizadeh Land parcel selection problems motivated by Red-Cockaded Woodpecker conservation problem 0.664130 2
n37 J. Aronson Fixed charge transportation problem 0.676810 3
allcolor Domenico Salvagnin Prepack optimization model. 0.691712 4
rmatr Dmitry Krushinsky Model coming from a formulation of the p-Median problem using square cost matrices 0.751762 5


Updated August 16, 2019