binkar10_1: Instance-to-Instance Comparison Results

Type: Instance
Submitter: H. Mittelmann
Description: Relaxed version of problem binkar10
MIPLIB Entry

Parent Instance (binkar10_1)

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

binkar10_1 Raw binkar10_1 Decomposed binkar10_1 Composite of MIC top 5 binkar10_1 Composite of MIPLIB top 5 binkar10_1 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-5260764-orauea decomposed allcolor10 decomposed allcolor58 decomposed neos-3581454-haast decomposed sing17 decomposed
Name neos-5260764-orauea [MIPLIB] allcolor10 [MIPLIB] allcolor58 [MIPLIB] neos-3581454-haast [MIPLIB] sing17 [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 / 0.774 2 / 0.817 3 / 0.819 4 / 0.831 5 / 0.840
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIC top 5.
neos-5260764-orauea raw allcolor10 raw allcolor58 raw neos-3581454-haast raw sing17 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.
shiftreg2-7 decomposed shiftreg5-1 decomposed neos-1396125 decomposed supportcase25 decomposed neos-1423785 decomposed
Name shiftreg2-7 [MIPLIB] shiftreg5-1 [MIPLIB] neos-1396125 [MIPLIB] supportcase25 [MIPLIB] neos-1423785 [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.
23 / 0.925 176 / 1.199 216 / 1.264 562 / 1.655 841 / 2.230
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIPLIB top 5.
shiftreg2-7 raw shiftreg5-1 raw neos-1396125 raw supportcase25 raw neos-1423785 raw

Instance Summary

The table below contains summary information for binkar10_1, the five most similar instances to binkar10_1 according to the MIC, and the five most similar instances to binkar10_1 according to MIPLIB 2017.

INSTANCE SUBMITTER DESCRIPTION ISS RANK
Parent Instance binkar10_1 [MIPLIB] H. Mittelmann Relaxed version of problem binkar10 0.000000 -
MIC Top 5 neos-5260764-orauea [MIPLIB] Hans Mittelmann Seem to be VRP output from 2-hour runs of Gurobi on 12 threads is included 0.774334 1
allcolor10 [MIPLIB] Domenico Salvagnin Prepack optimization instance. 0.816583 2
allcolor58 [MIPLIB] Domenico Salvagnin Prepack optimization model. 0.819467 3
neos-3581454-haast [MIPLIB] Jeff Linderoth (None provided) 0.830706 4
sing17 [MIPLIB] Daniel Espinoza Imported from the MIPLIB2010 submissions. 0.840261 5
MIPLIB Top 5 shiftreg2-7 [MIPLIB] Domenico Salvagnin Multi-activity shift scheduling problem with 2 activities and 12 employees, using an implicit model based on a regular language. 0.925343 23
shiftreg5-1 [MIPLIB] Domenico Salvagnin Multi-activity shift scheduling problem with 5 activities and 24 employees, using an implicit model based on a regular language. 1.198842 176
neos-1396125 [MIPLIB] NEOS Server Submission Instance coming from the NEOS Server with unknown application 1.263962 216
supportcase25 [MIPLIB] Michael Winkler MIP instances collected from Gurobi forum with unknown application 1.654563 562
neos-1423785 [MIPLIB] NEOS Server Submission Imported from the MIPLIB2010 submissions. 2.230184 841


binkar10_1: Instance-to-Model Comparison Results

Model Group Assignment from MIPLIB: no model group assignment
Assigned Model Group Rank/ISS in the MIC: N.A. / N.A.

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: allcolor Model group: map Model group: polygonpack Model group: ustun
Name rmatr allcolor map 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 / 1.008 2 / 1.056 3 / 1.057 4 / 1.107 5 / 1.138

Model Group Summary

The table below contains summary information for the five most similar model groups to binkar10_1 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 1.008210 1
allcolor Domenico Salvagnin Prepack optimization model. 1.056428 2
map Kiyan Ahmadizadeh Land parcel selection problems motivated by Red-Cockaded Woodpecker conservation problem 1.057311 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. 1.106993 4
ustun Berk Ustun MIP to create optimized data-driven scoring systems. See: https://github.com/ustunb/miplib2017-slim#miplib2017-slim for a description. 1.137784 5