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usAbbrv-8-25_70: Instance-to-Instance Comparison Results
| Type: | Instance |
| Submitter: | publicly available |
| Description: | Imported from MIPLIB2010. |
| MIPLIB Entry |
Parent Instance (usAbbrv-8-25_70)
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 | berlin_5_8_0 [MIPLIB] | railway_8_1_0 [MIPLIB] | stein15inf [MIPLIB] | stein45inf [MIPLIB] | ns2034125 [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 / 0.613 | 2 / 1.079 | 3 / 1.184 | 4 / 1.185 | 5 / 1.195 | |
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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 | berlin_5_8_0 [MIPLIB] | railway_8_1_0 [MIPLIB] | CMS750_4 [MIPLIB] | pigeon-20 [MIPLIB] | pigeon-16 [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 / 0.613 | 2 / 1.079 | 6 / 1.212 | 760 / 2.015 | 768 / 2.041 | |
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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 usAbbrv-8-25_70, the five most similar instances to usAbbrv-8-25_70 according to the MIC, and the five most similar instances to usAbbrv-8-25_70 according to MIPLIB 2017.
| INSTANCE | SUBMITTER | DESCRIPTION | ISS | RANK | |
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| Parent Instance | usAbbrv-8-25_70 [MIPLIB] | publicly available | Imported from MIPLIB2010. | 0.000000 | - |
| MIC Top 5 | berlin_5_8_0 [MIPLIB] | G. Klau | Railway optimization problems. The problem was solved using CPLEX 12.3 on a 32 core Sun Galaxy 4600 machine, equipped with eight Quad-Core AMD Opteron 8384 processors at 2.7 GHz and 512 GB RAM. It took approximately 9 hours. The problem was solved using CPLEX 12.4 in about 55 minutes (May 2014). | 0.613279 | 1 |
| railway_8_1_0 [MIPLIB] | MIPLIB submission pool | Imported from the MIPLIB2010 submissions. | 1.079413 | 2 | |
| stein15inf [MIPLIB] | MIPLIB submission pool | Imported from the MIPLIB2010 submissions. | 1.184107 | 3 | |
| stein45inf [MIPLIB] | MIPLIB submission pool | Imported from the MIPLIB2010 submissions. | 1.184507 | 4 | |
| ns2034125 [MIPLIB] | NEOS Server Submission | Imported from the MIPLIB2010 submissions. | 1.195491 | 5 | |
| MIPLIB Top 5 | berlin_5_8_0 [MIPLIB] | G. Klau | Railway optimization problems. The problem was solved using CPLEX 12.3 on a 32 core Sun Galaxy 4600 machine, equipped with eight Quad-Core AMD Opteron 8384 processors at 2.7 GHz and 512 GB RAM. It took approximately 9 hours. The problem was solved using CPLEX 12.4 in about 55 minutes (May 2014). | 0.613279 | 1 |
| railway_8_1_0 [MIPLIB] | MIPLIB submission pool | Imported from the MIPLIB2010 submissions. | 1.079413 | 2 | |
| CMS750_4 [MIPLIB] | MIPLIB submission pool | Imported from the MIPLIB2010 submissions. | 1.212361 | 6 | |
| pigeon-20 [MIPLIB] | Sam Allen | Instance of 3D packing (container loading) problem | 2.015470 | 760 | |
| pigeon-16 [MIPLIB] | Sam Allen | Instance of 3D packing (container loading) problem | 2.041053 | 768 |
usAbbrv-8-25_70: 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 | stein | scp | markshare | neos-pseudoapplication-109 | supportvectormachine | |
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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 / 1.669 | 2 / 1.760 | 3 / 1.810 | 4 / 1.920 | 5 / 1.949 |
Model Group Summary
The table below contains summary information for the five most similar model groups to usAbbrv-8-25_70 according to the MIC.
| MODEL GROUP | SUBMITTER | DESCRIPTION | ISS | RANK | |
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| MIC Top 5 | stein | MIPLIB submission pool | Imported from the MIPLIB2010 submissions. | 1.669359 | 1 |
| 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 | 1.760368 | 2 | |
| markshare | G. Cornuéjols, M. Dawande | Market sharing problem | 1.810263 | 3 | |
| neos-pseudoapplication-109 | Jeff Linderoth | (None provided) | 1.920060 | 4 | |
| supportvectormachine | Toni Sorrell | Suport vector machine with ramp loss. GSVM2-RL is the formulation found in Hess E. and Brooks P. (2015) paper, The Support Vector Machine and Mixed Integer Linear Programming: Ramp Loss SVM with L1-Norm Regularization | 1.949052 | 5 |
