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ic97_tension: Instance-to-Instance Comparison Results
Type: | Instance |
Submitter: | MIPLIB submission pool |
Description: | Imported from the MIPLIB2010 submissions. |
MIPLIB Entry |
Parent Instance (ic97_tension)
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-2991472-kalu [MIPLIB] | b2c1s1 [MIPLIB] | bg512142 [MIPLIB] | opt1217 [MIPLIB] | a2c1s1 [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 / 0.943 | 2 / 1.001 | 3 / 1.001 | 4 / 1.022 | 5 / 1.028 | |
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 | timtab1CUTS [MIPLIB] | neos-4954672-berkel [MIPLIB] | csched008 [MIPLIB] | csched007 [MIPLIB] | icir97_tension [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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31 / 1.119 | 32 / 1.121 | 446 / 1.419 | 451 / 1.423 | 852 / 1.947 | |
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 ic97_tension, the five most similar instances to ic97_tension according to the MIC, and the five most similar instances to ic97_tension according to MIPLIB 2017.
INSTANCE | SUBMITTER | DESCRIPTION | ISS | RANK | |
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Parent Instance | ic97_tension [MIPLIB] | MIPLIB submission pool | Imported from the MIPLIB2010 submissions. | 0.000000 | - |
MIC Top 5 | neos-2991472-kalu [MIPLIB] | Jeff Linderoth | (None provided) | 0.943012 | 1 |
b2c1s1 [MIPLIB] | M. Vyve, Y. Pochet | Lot sizing instance. Solved by Gurobi 4.6.1 (12 threads) in 116575 seconds (January 2012). | 1.001262 | 2 | |
bg512142 [MIPLIB] | A. Miller | Multilevel lot-sizing instance. | 1.001266 | 3 | |
opt1217 [MIPLIB] | MIPLIB submission pool | Imported from the MIPLIB2010 submissions. | 1.021849 | 4 | |
a2c1s1 [MIPLIB] | M. Vyve, Y. Pochet | Lot sizing instance. | 1.027898 | 5 | |
MIPLIB Top 5 | timtab1CUTS [MIPLIB] | C. Liebchen, R. Möhring | Public transport scheduling problem | 1.118955 | 31 |
neos-4954672-berkel [MIPLIB] | Jeff Linderoth | (None provided) | 1.121161 | 32 | |
csched008 [MIPLIB] | Tallys Yunes | Cumulative scheduling problem instance | 1.419162 | 446 | |
csched007 [MIPLIB] | Tallys Yunes | Cumulative scheduling problem instance | 1.422503 | 451 | |
icir97_tension [MIPLIB] | MIPLIB submission pool | Imported from the MIPLIB2010 submissions. | 1.946727 | 852 |
ic97_tension: 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 | pfour | neos-pseudoapplication-74 | timtab | scp | neos-pseudoapplication-40 | |
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 / 1.350 | 2 / 1.453 | 3 / 1.460 | 4 / 1.463 | 5 / 1.473 |
Model Group Summary
The table below contains summary information for the five most similar model groups to ic97_tension according to the MIC.
MODEL GROUP | SUBMITTER | DESCRIPTION | ISS | RANK | |
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MIC Top 5 | pfour | MIPLIB submission pool | Imported from the MIPLIB2010 submissions. | 1.349535 | 1 |
neos-pseudoapplication-74 | Jeff Linderoth | (None provided) | 1.453190 | 2 | |
timtab | C. Liebchen, R. Möhring | Public transport scheduling problem | 1.460254 | 3 | |
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 | 1.463200 | 4 | |
neos-pseudoapplication-40 | Jeff Linderoth | (None provided) | 1.472837 | 5 |