neos-3046615-murg: Instance-to-Instance Comparison Results

Type: Instance
Submitter: Jeff Linderoth
Description: (None provided)
MIPLIB Entry

Parent Instance (neos-3046615-murg)

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

neos-3046615-murg Raw neos-3046615-murg Decomposed neos-3046615-murg Composite of MIC top 5 neos-3046615-murg Composite of MIPLIB top 5 neos-3046615-murg 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-3046601-motu decomposed rmatr100-p10 decomposed neos-3209462-rhin decomposed rmatr100-p5 decomposed rmatr200-p10 decomposed
Name neos-3046601-motu [MIPLIB] rmatr100-p10 [MIPLIB] neos-3209462-rhin [MIPLIB] rmatr100-p5 [MIPLIB] rmatr200-p10 [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 / 0.204 2 / 0.477 3 / 0.488 4 / 0.490 5 / 0.502
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIC top 5.
neos-3046601-motu raw rmatr100-p10 raw neos-3209462-rhin raw rmatr100-p5 raw rmatr200-p10 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.
neos-3046601-motu decomposed neos16 decomposed neos-3009394-lami decomposed timtab1CUTS decomposed neos-4338804-snowy decomposed
Name neos-3046601-motu [MIPLIB] neos16 [MIPLIB] neos-3009394-lami [MIPLIB] timtab1CUTS [MIPLIB] neos-4338804-snowy [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 / 0.204 15 / 0.589 249 / 1.197 493 / 1.491 666 / 1.756
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIPLIB top 5.
neos-3046601-motu raw neos16 raw neos-3009394-lami raw timtab1CUTS raw neos-4338804-snowy raw

Instance Summary

The table below contains summary information for neos-3046615-murg, the five most similar instances to neos-3046615-murg according to the MIC, and the five most similar instances to neos-3046615-murg according to MIPLIB 2017.

INSTANCE SUBMITTER DESCRIPTION ISS RANK
Parent Instance neos-3046615-murg [MIPLIB] Jeff Linderoth (None provided) 0.000000 -
MIC Top 5 neos-3046601-motu [MIPLIB] Jeff Linderoth (None provided) 0.203888 1
rmatr100-p10 [MIPLIB] Dmitry Krushinsky Instance coming from a formulation of the p-Median problem using square cost matrices 0.477119 2
neos-3209462-rhin [MIPLIB] Jeff Linderoth (None provided) 0.488377 3
rmatr100-p5 [MIPLIB] Dmitry Krushinsky Instance coming from a formulation of the p-Median problem using square cost matrices 0.490131 4
rmatr200-p10 [MIPLIB] Dmitry Krushinsky Instance coming from a formulation of the p-Median problem using square cost matrices. Solved by Gurobi 4.6.1 (12 threads) in 19644 seconds (January 2012). 0.502237 5
MIPLIB Top 5 neos-3046601-motu [MIPLIB] Jeff Linderoth (None provided) 0.203888 1
neos16 [MIPLIB] NEOS Server Submission Instance coming from the NEOS Server with unknown application 0.589107 15
neos-3009394-lami [MIPLIB] Jeff Linderoth (None provided) 1.196902 249
timtab1CUTS [MIPLIB] C. Liebchen, R. Möhring Public transport scheduling problem 1.490771 493
neos-4338804-snowy [MIPLIB] Jeff Linderoth (None provided) 1.756231 666


neos-3046615-murg: Instance-to-Model Comparison Results

Model Group Assignment from MIPLIB: neos-pseudoapplication-90
Assigned Model Group Rank/ISS in the MIC: 18 / 1.532

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: rmatr Model group: map Model group: neos-pseudoapplication-54 Model group: polygonpack Model group: ustun
Name rmatr map neos-pseudoapplication-54 polygonpack ustun
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 / 0.811 2 / 0.924 3 / 0.938 4 / 1.107 5 / 1.198

Model Group Summary

The table below contains summary information for the five most similar model groups to neos-3046615-murg according to the MIC.

MODEL GROUP SUBMITTER DESCRIPTION ISS RANK
MIC Top 5 rmatr Dmitry Krushinsky Model coming from a formulation of the p-Median problem using square cost matrices 0.810598 1
map Kiyan Ahmadizadeh Land parcel selection problems motivated by Red-Cockaded Woodpecker conservation problem 0.923651 2
neos-pseudoapplication-54 Jeff Linderoth (None provided) 0.937628 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. 1.106864 4
ustun Berk Ustun MIP to create optimized data-driven scoring systems. See: https://github.com/ustunb/miplib2017-slim#miplib2017-slim for a description. 1.197527 5