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neos-5093327-huahum: Instance-to-Instance Comparison Results
Type: | Instance |
Submitter: | Jeff Linderoth |
Description: | (None provided) |
MIPLIB Entry |
Parent Instance (neos-5093327-huahum)
All other instances below were be compared against this "query" instance.![]() ![]() |
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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-913984 [MIPLIB] | nexp-50-20-1-1 [MIPLIB] | beasleyC1 [MIPLIB] | beasleyC3 [MIPLIB] | neos9 [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 / 0.437 | 2 / 0.443 | 3 / 0.467 | 4 / 0.477 | 5 / 0.478 | |
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 | neos-5102383-irwell [MIPLIB] | neos-5100895-inster [MIPLIB] | neos-5076235-embley [MIPLIB] | neos-5079731-flyers [MIPLIB] | maritime-jg3d9 [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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209 / 1.034 | 238 / 1.094 | 259 / 1.122 | 279 / 1.149 | 507 / 1.448 | |
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 neos-5093327-huahum, the five most similar instances to neos-5093327-huahum according to the MIC, and the five most similar instances to neos-5093327-huahum according to MIPLIB 2017.
INSTANCE | SUBMITTER | DESCRIPTION | ISS | RANK | |
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Parent Instance | neos-5093327-huahum [MIPLIB] | Jeff Linderoth | (None provided) | 0.000000 | - |
MIC Top 5 | neos-913984 [MIPLIB] | NEOS Server Submission | Imported from the MIPLIB2010 submissions. | 0.437421 | 1 |
nexp-50-20-1-1 [MIPLIB] | MIPLIB submission pool | Imported from the MIPLIB2010 submissions. | 0.442622 | 2 | |
beasleyC1 [MIPLIB] | F. Ortega, L. Wolsey | Fixed cost network flow problems | 0.466761 | 3 | |
beasleyC3 [MIPLIB] | F. Ortega, L. Wolsey | Fixed cost network flow problems | 0.476769 | 4 | |
neos9 [MIPLIB] | NEOS Server Submission | Imported from the MIPLIB2010 submissions. | 0.477773 | 5 | |
MIPLIB Top 5 | neos-5102383-irwell [MIPLIB] | Jeff Linderoth | (None provided) | 1.034345 | 209 |
neos-5100895-inster [MIPLIB] | Jeff Linderoth | (None provided) | 1.093588 | 238 | |
neos-5076235-embley [MIPLIB] | Jeff Linderoth | (None provided) | 1.121718 | 259 | |
neos-5079731-flyers [MIPLIB] | Jeff Linderoth | (None provided) | 1.148549 | 279 | |
maritime-jg3d9 [MIPLIB] | Dimitri Papageorgiou | Maritime Inventory Routing Problems: Jiang-Grossmann Instances. These instances are available at https://mirplib.scl.gatech.edu/instances, along with a host of additional information such as the underlying data used to generate the model, best known upper and lower bounds, and more. They involve a single product maritime inventory routing problem and explore the use of continuous and discrete time models. A continuous-time model based on time slots for single docks is used for some instances. A model based on event points to handle parallel docks is used in others. A discrete time model based on a single commodity fixed-charge network flow problem (FCNF) is used for other instances. All the models are solved for multiple randomly generated instances of different problems to compare their computational efficiency. | 1.448400 | 507 |
neos-5093327-huahum: Instance-to-Model Comparison Results
Model Group Assignment from MIPLIB: | neos-pseudoapplication-17 |
Assigned Model Group Rank/ISS in the MIC: | 68 / 2.022 |
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 | beasley | neos-pseudoapplication-2 | noip | ab | aflow | |
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 / 0.707 | 2 / 0.749 | 3 / 0.886 | 4 / 0.937 | 5 / 0.937 |
Model Group Summary
The table below contains summary information for the five most similar model groups to neos-5093327-huahum according to the MIC.
MODEL GROUP | SUBMITTER | DESCRIPTION | ISS | RANK | |
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MIC Top 5 | beasley | F. Ortega, L. Wolsey | Fixed cost network flow problems | 0.706665 | 1 |
neos-pseudoapplication-2 | NEOS Server Submission | Imported from the MIPLIB2010 submissions. | 0.749043 | 2 | |
noip | Christopher Hojny | integer programming formulation that verifies that no integer programming formulation of a given 0/1-point set exists | 0.886083 | 3 | |
ab | MIPLIB submission pool | Imported from the MIPLIB2010 submissions. | 0.936609 | 4 | |
aflow | T. Achterberg | Arborescence flow problem on a graph with 40 nodes and edge density 0.9 | 0.936658 | 5 |