ns2124243: Instance-to-Instance Comparison Results

Type: Instance
Submitter: Timo Berthold
Description: Instance coming from the NEOS Server with unknown application
MIPLIB Entry

Parent Instance (ns2124243)

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

ns2124243 Raw ns2124243 Decomposed ns2124243 Composite of MIC top 5 ns2124243 Composite of MIPLIB top 5 ns2124243 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 graph40-40-1rand decomposed ns2122698 decomposed graph40-80-1rand decomposed rmatr200-p20 decomposed
Name neos-4703857-ahuroa [MIPLIB] graph40-40-1rand [MIPLIB] ns2122698 [MIPLIB] graph40-80-1rand [MIPLIB] rmatr200-p20 [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 / 0.673 2 / 0.687 3 / 0.692 4 / 0.700 5 / 0.717
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 graph40-40-1rand raw ns2122698 raw graph40-80-1rand raw rmatr200-p20 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.
ns2122698 decomposed neos-3660371-kurow decomposed uccase7 decomposed uccase9 decomposed uccase10 decomposed
Name ns2122698 [MIPLIB] neos-3660371-kurow [MIPLIB] uccase7 [MIPLIB] uccase9 [MIPLIB] uccase10 [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.
3 / 0.692 76 / 0.892 584 / 1.606 611 / 1.660 768 / 2.000
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIPLIB top 5.
ns2122698 raw neos-3660371-kurow raw uccase7 raw uccase9 raw uccase10 raw

Instance Summary

The table below contains summary information for ns2124243, the five most similar instances to ns2124243 according to the MIC, and the five most similar instances to ns2124243 according to MIPLIB 2017.

INSTANCE SUBMITTER DESCRIPTION ISS RANK
Parent Instance ns2124243 [MIPLIB] Timo Berthold Instance coming from the NEOS Server with unknown application 0.000000 -
MIC Top 5 neos-4703857-ahuroa [MIPLIB] Jeff Linderoth (None provided) 0.672755 1
graph40-40-1rand [MIPLIB] Michael Bastubbe Packing Cuts in Undirected Graphs. Instances are described in 4.1. 0.686717 2
ns2122698 [MIPLIB] Timo Berthold Instance coming from the NEOS Server with unknown application. Solved by SCIP-CPLEX in 9500 seconds. 0.691603 3
graph40-80-1rand [MIPLIB] Michael Bastubbe Packing Cuts in Undirected Graphs. Instances are described in 4.1. 0.700437 4
rmatr200-p20 [MIPLIB] Dmitry Krushinsky Instance coming from a formulation of the p-Median problem using square cost matrices. Solved using ug[SCIP/spx], a distributed massively parallel version of SCIP run on 2,000 cores at the HLRN-II super computer facility. 0.717468 5
MIPLIB Top 5 ns2122698 [MIPLIB] Timo Berthold Instance coming from the NEOS Server with unknown application. Solved by SCIP-CPLEX in 9500 seconds. 0.691603 3
neos-3660371-kurow [MIPLIB] Jeff Linderoth (None provided) 0.891932 76
uccase7 [MIPLIB] Daniel Espinoza Imported from the MIPLIB2010 submissions. 1.606407 584
uccase9 [MIPLIB] Daniel Espinoza Imported from the MIPLIB2010 submissions. 1.660111 611
uccase10 [MIPLIB] Daniel Espinoza Imported from the MIPLIB2010 submissions. 2.000239 768


ns2124243: Instance-to-Model Comparison Results

Model Group Assignment from MIPLIB: neos-pseudoapplication-93
Assigned Model Group Rank/ISS in the MIC: 125 / 2.762

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: allcolor Model group: sp_product Model group: polygonpack
Name map rmatr allcolor 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 / 1.014 2 / 1.065 3 / 1.217 4 / 1.234 5 / 1.249

Model Group Summary

The table below contains summary information for the five most similar model groups to ns2124243 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 1.014336 1
rmatr Dmitry Krushinsky Model coming from a formulation of the p-Median problem using square cost matrices 1.065025 2
allcolor Domenico Salvagnin Prepack optimization model. 1.216619 3
sp_product MIPLIB submission pool Imported from the MIPLIB2010 submissions. 1.234304 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. 1.248716 5