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enlight_hard: Instance-to-Instance Comparison Results
| Type: | Instance |
| Submitter: | A. Zymolka |
| Description: | Model to solve instance of a combinatorial game ``EnLight'' Imported from the MIPLIB2010 submissions. |
| MIPLIB Entry |
Parent Instance (enlight_hard)
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 | enlight11 [MIPLIB] | enlight9 [MIPLIB] | enlight4 [MIPLIB] | flugplinf [MIPLIB] | g503inf [MIPLIB] | |
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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 / 0.422 | 2 / 0.492 | 3 / 0.766 | 4 / 0.835 | 5 / 0.848 | |
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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 | enlight11 [MIPLIB] | enlight9 [MIPLIB] | enlight4 [MIPLIB] | enlight8 [MIPLIB] | timtab1 [MIPLIB] | |
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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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1 / 0.422 | 2 / 0.492 | 3 / 0.766 | 56 / 1.076 | 76 / 1.100 | |
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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 enlight_hard, the five most similar instances to enlight_hard according to the MIC, and the five most similar instances to enlight_hard according to MIPLIB 2017.
| INSTANCE | SUBMITTER | DESCRIPTION | ISS | RANK | |
|---|---|---|---|---|---|
| Parent Instance | enlight_hard [MIPLIB] | A. Zymolka | Model to solve instance of a combinatorial game ``EnLight'' Imported from the MIPLIB2010 submissions. | 0.000000 | - |
| MIC Top 5 | enlight11 [MIPLIB] | A. Zymolka | Model to solve instance of a combinatorial game ``EnLight'' Imported from the MIPLIB2010 submissions. | 0.421960 | 1 |
| enlight9 [MIPLIB] | A. Zymolka | Model to solve instance of a combinatorial game ``EnLight'' | 0.492352 | 2 | |
| enlight4 [MIPLIB] | A. Zymolka | Model to solve instance of a combinatorial game ``EnLight'' Imported from the MIPLIB2010 submissions. | 0.765641 | 3 | |
| flugplinf [MIPLIB] | MIPLIB submission pool | Imported from the MIPLIB2010 submissions. | 0.834837 | 4 | |
| g503inf [MIPLIB] | MIPLIB submission pool | Imported from the MIPLIB2010 submissions. | 0.848261 | 5 | |
| MIPLIB Top 5 | enlight11 [MIPLIB] | A. Zymolka | Model to solve instance of a combinatorial game ``EnLight'' Imported from the MIPLIB2010 submissions. | 0.421960 | 1 |
| enlight9 [MIPLIB] | A. Zymolka | Model to solve instance of a combinatorial game ``EnLight'' | 0.492352 | 2 | |
| enlight4 [MIPLIB] | A. Zymolka | Model to solve instance of a combinatorial game ``EnLight'' Imported from the MIPLIB2010 submissions. | 0.765641 | 3 | |
| enlight8 [MIPLIB] | A. Zymolka | Model to solve instance of a combinatorial game ``EnLight'' Imported from the MIPLIB2010 submissions. | 1.075779 | 56 | |
| timtab1 [MIPLIB] | C. Liebchen, R. Möhring | Public transport scheduling problem | 1.100057 | 76 |
enlight_hard: Instance-to-Model Comparison Results
| Model Group Assignment from MIPLIB: | enlight |
| Assigned Model Group Rank/ISS in the MIC: | 1 / 1.144 |
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 | enlight | neos-pseudoapplication-74 | scp | markshare | stein | |
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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 / 1.145 | 2 / 1.160 | 3 / 1.330 | 4 / 1.385 | 5 / 1.447 |
Model Group Summary
The table below contains summary information for the five most similar model groups to enlight_hard according to the MIC.
| MODEL GROUP | SUBMITTER | DESCRIPTION | ISS | RANK | |
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| MIC Top 5 | enlight | A. Zymolka | Model to solve model of a combinatorial game ``EnLight'' Imported from the MIPLIB2010 submissions. | 1.144854 | 1 |
| neos-pseudoapplication-74 | Jeff Linderoth | (None provided) | 1.159804 | 2 | |
| scp | Shunji Umetani | This is a random test model generator for SCP using the scheme of the following paper, namely the column cost c[j] are integer randomly generated from [1,100]; every column covers at least one row; and every row is covered by at least two columns. see reference: E. Balas and A. Ho, Set covering algorithms using cutting planes, heuristics, and subgradient optimization: A computational study, Mathematical Programming, 12 (1980), 37-60. We have newly generated Classes I-N with the following parameter values, where each class has five models. We have also generated reduced models by a standard pricing method in the following paper: S. Umetani and M. Yagiura, Relaxation heuristics for the set covering problem, Journal of the Operations Research Society of Japan, 50 (2007), 350-375. You can obtain the model generator program from the following web site. https://sites.google.com/site/shunjiumetani/benchmark | 1.329598 | 3 | |
| markshare | G. Cornuéjols, M. Dawande | Market sharing problem | 1.384966 | 4 | |
| stein | MIPLIB submission pool | Imported from the MIPLIB2010 submissions. | 1.447305 | 5 |
