graph40-20-1rand: Instance-to-Instance Comparison Results

Type: Instance
Submitter: Michael Bastubbe
Description: Packing Cuts in Undirected Graphs. Instances are described in 4.1.
MIPLIB Entry

Parent Instance (graph40-20-1rand)

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

graph40-20-1rand Raw graph40-20-1rand Decomposed graph40-20-1rand Composite of MIC top 5 graph40-20-1rand Composite of MIPLIB top 5 graph40-20-1rand 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.
graph20-80-1rand decomposed neos-876808 decomposed thor50dday decomposed ns1430538 decomposed neos-824661 decomposed
Name graph20-80-1rand [MIPLIB] neos-876808 [MIPLIB] thor50dday [MIPLIB] ns1430538 [MIPLIB] neos-824661 [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 / 0.222 2 / 0.272 3 / 0.309 4 / 0.348 5 / 0.354
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIC top 5.
graph20-80-1rand raw neos-876808 raw thor50dday raw ns1430538 raw neos-824661 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.
graph20-80-1rand decomposed graph40-40-1rand decomposed graph40-80-1rand decomposed graph20-20-1rand decomposed neos-3555904-turama decomposed
Name graph20-80-1rand [MIPLIB] graph40-40-1rand [MIPLIB] graph40-80-1rand [MIPLIB] graph20-20-1rand [MIPLIB] neos-3555904-turama [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 / 0.222 9 / 0.383 22 / 0.404 78 / 0.612 521 / 1.475
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIPLIB top 5.
graph20-80-1rand raw graph40-40-1rand raw graph40-80-1rand raw graph20-20-1rand raw neos-3555904-turama raw

Instance Summary

The table below contains summary information for graph40-20-1rand, the five most similar instances to graph40-20-1rand according to the MIC, and the five most similar instances to graph40-20-1rand according to MIPLIB 2017.

INSTANCE SUBMITTER DESCRIPTION ISS RANK
Parent Instance graph40-20-1rand [MIPLIB] Michael Bastubbe Packing Cuts in Undirected Graphs. Instances are described in 4.1. 0.000000 -
MIC Top 5 graph20-80-1rand [MIPLIB] Michael Bastubbe Packing Cuts in Undirected Graphs. Instances are described in 4.1. 0.222364 1
neos-876808 [MIPLIB] NEOS Server Submission Imported from the MIPLIB2010 submissions. 0.271775 2
thor50dday [MIPLIB] Daniel Rehfeldt Steiner tree problem in graphs instance, consisting of a complete graph with 231 vertices of which 50 are terminals. The vertices correspond to cities (mostly capitals) around the world, the edges weights correspond to the distances in km. 0.308501 3
ns1430538 [MIPLIB] NEOS Server Submission Instance coming from the NEOS Server with unknown application. 0.348327 4
neos-824661 [MIPLIB] NEOS Server Submission Instance coming from the NEOS Server with unknown application 0.353993 5
MIPLIB Top 5 graph20-80-1rand [MIPLIB] Michael Bastubbe Packing Cuts in Undirected Graphs. Instances are described in 4.1. 0.222364 1
graph40-40-1rand [MIPLIB] Michael Bastubbe Packing Cuts in Undirected Graphs. Instances are described in 4.1. 0.383185 9
graph40-80-1rand [MIPLIB] Michael Bastubbe Packing Cuts in Undirected Graphs. Instances are described in 4.1. 0.404399 22
graph20-20-1rand [MIPLIB] Michael Bastubbe Packing Cuts in Undirected Graphs. Instances are described in 4.1. 0.611732 78
neos-3555904-turama [MIPLIB] Hans Mittelmann Collection of anonymous submissions to the NEOS Server for Optimization 1.475257 521


graph40-20-1rand: Instance-to-Model Comparison Results

Model Group Assignment from MIPLIB: graphs
Assigned Model Group Rank/ISS in the MIC: 5 / 0.696

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: n37 Model group: polygonpack Model group: graphs
Name map rmatr n37 polygonpack graphs
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 / 0.568 2 / 0.580 3 / 0.593 4 / 0.613 5 / 0.697

Model Group Summary

The table below contains summary information for the five most similar model groups to graph40-20-1rand 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 0.568315 1
rmatr Dmitry Krushinsky Model coming from a formulation of the p-Median problem using square cost matrices 0.579991 2
n37 J. Aronson Fixed charge transportation problem 0.592762 3
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. 0.612633 4
graphs Michael Bastubbe Packing Cuts in Undirected Graphs. Models are described in 4.1. 0.696527 5