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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.
Raw
This is the CCM image before the decomposition procedure has been applied.
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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.
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Composite of MIC Top 5
Composite of the five decomposed CCM images from the MIC Top 5.
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Composite of MIPLIB Top 5
Composite of the five decomposed CCM images from the MIPLIB Top 5.
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Model Group Composite Image
Composite of the decomposed CCM images for every instance in the same model group as this query.
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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.
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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.
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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.
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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.
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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.
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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.
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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 | |
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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.
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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.
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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 | |
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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 |