sing44: Instance-to-Instance Comparison Results

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

Parent Instance (sing44)

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

sing44 Raw sing44 Decomposed sing44 Composite of MIC top 5 sing44 Composite of MIPLIB top 5 sing44 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.
sing326 decomposed neos-941313 decomposed sing5 decomposed neos22 decomposed sing11 decomposed
Name sing326 [MIPLIB] neos-941313 [MIPLIB] sing5 [MIPLIB] neos22 [MIPLIB] sing11 [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 / 0.344 2 / 0.371 3 / 0.406 4 / 0.407 5 / 0.414
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIC top 5.
sing326 raw neos-941313 raw sing5 raw neos22 raw sing11 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.
sing326 decomposed uccase8 decomposed uccase7 decomposed uccase9 decomposed lr2-22dr3-333vc4v17a-t60 decomposed
Name sing326 [MIPLIB] uccase8 [MIPLIB] uccase7 [MIPLIB] uccase9 [MIPLIB] lr2-22dr3-333vc4v17a-t60 [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 / 0.344 606 / 1.697 644 / 1.759 678 / 1.809 945 / 3.013
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIPLIB top 5.
sing326 raw uccase8 raw uccase7 raw uccase9 raw lr2-22dr3-333vc4v17a-t60 raw

Instance Summary

The table below contains summary information for sing44, the five most similar instances to sing44 according to the MIC, and the five most similar instances to sing44 according to MIPLIB 2017.

INSTANCE SUBMITTER DESCRIPTION ISS RANK
Parent Instance sing44 [MIPLIB] Daniel Espinoza Imported from the MIPLIB2010 submissions. 0.000000 -
MIC Top 5 sing326 [MIPLIB] Daniel Espinoza Imported from the MIPLIB2010 submissions. 0.344045 1
neos-941313 [MIPLIB] NEOS Server Submission Instance coming from the NEOS Server with unknown application 0.370772 2
sing5 [MIPLIB] Daniel Espinoza Imported from the MIPLIB2010 submissions. 0.405978 3
neos22 [MIPLIB] NEOS Server Submission Imported from the MIPLIB2010 submissions. 0.407226 4
sing11 [MIPLIB] Daniel Espinoza Imported from the MIPLIB2010 submissions. 0.414270 5
MIPLIB Top 5 sing326 [MIPLIB] Daniel Espinoza Imported from the MIPLIB2010 submissions. 0.344045 1
uccase8 [MIPLIB] Daniel Espinoza Imported from the MIPLIB2010 submissions. 1.697283 606
uccase7 [MIPLIB] Daniel Espinoza Imported from the MIPLIB2010 submissions. 1.758558 644
uccase9 [MIPLIB] Daniel Espinoza Imported from the MIPLIB2010 submissions. 1.808699 678
lr2-22dr3-333vc4v17a-t60 [MIPLIB] Dimitri Papageorgiou Maritime Inventory Routing Problem Library - Group 1 Instances. These instances are available at https://mirplib.scl.gatech.edu/instances, along with a host of additional information such as the underlying data used to generate the model, best known upper and lower bounds, and more. As of 2012, Group 1 instances gave Cplex and Gurobi tremendous difficulty finding a single feasible solution. 3.012755 945


sing44: Instance-to-Model Comparison Results

Model Group Assignment from MIPLIB: sing
Assigned Model Group Rank/ISS in the MIC: 5 / 0.676

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: graphs Model group: neos-pseudoapplication-27 Model group: polygonpack Model group: n37 Model group: sing
Name graphs neos-pseudoapplication-27 polygonpack n37 sing
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 / 0.551 2 / 0.581 3 / 0.670 4 / 0.671 5 / 0.677

Model Group Summary

The table below contains summary information for the five most similar model groups to sing44 according to the MIC.

MODEL GROUP SUBMITTER DESCRIPTION ISS RANK
MIC Top 5 graphs Michael Bastubbe Packing Cuts in Undirected Graphs. Models are described in 4.1. 0.550631 1
neos-pseudoapplication-27 NEOS Server Submission Imported from the MIPLIB2010 submissions. 0.581038 2
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. 0.670360 3
n37 J. Aronson Fixed charge transportation problem 0.670739 4
sing Daniel Espinoza Imported from the MIPLIB2010 submissions. 0.676503 5