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physiciansched3-4: Instance-to-Instance Comparison Results
| Type: | Instance |
| Submitter: | Pelin Damci-Kurt |
| Description: | Physician scheduling problem for hospitalist, radiology and kidney specialist groups. |
| MIPLIB Entry |
Parent Instance (physiciansched3-4)
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 | physiciansched3-3 [MIPLIB] | neos-3402294-bobin [MIPLIB] | icir97_potential [MIPLIB] | physiciansched6-1 [MIPLIB] | comp12-2idx [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 / 0.810 | 2 / 1.310 | 3 / 1.339 | 4 / 1.374 | 5 / 1.384 | |
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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 | physiciansched3-3 [MIPLIB] | physiciansched5-3 [MIPLIB] | neos-555884 [MIPLIB] | neos-5193246-nerang [MIPLIB] | neos-5195221-niemur* [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 / 0.810 | 44 / 1.734 | 467 / 2.005 | 516 / 2.018 | 516* / 2.018* | |
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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 physiciansched3-4, the five most similar instances to physiciansched3-4 according to the MIC, and the five most similar instances to physiciansched3-4 according to MIPLIB 2017.
| INSTANCE | SUBMITTER | DESCRIPTION | ISS | RANK | |
|---|---|---|---|---|---|
| Parent Instance | physiciansched3-4 [MIPLIB] | Pelin Damci-Kurt | Physician scheduling problem for hospitalist, radiology and kidney specialist groups. | 0.000000 | - |
| MIC Top 5 | physiciansched3-3 [MIPLIB] | Pelin Damci-Kurt | Physician scheduling problem for hospitalist, radiology and kidney specialist groups. | 0.809600 | 1 |
| neos-3402294-bobin [MIPLIB] | Jeff Linderoth | (None provided) | 1.309991 | 2 | |
| icir97_potential [MIPLIB] | MIPLIB submission pool | Imported from the MIPLIB2010 submissions. | 1.338548 | 3 | |
| physiciansched6-1 [MIPLIB] | Pelin Damci-Kurt | Physician scheduling problem for hospitalist, radiology and kidney specialist groups. | 1.374293 | 4 | |
| comp12-2idx [MIPLIB] | Matias Sørensen | Instances comp01-21 of curriculum based course timetabling from the International Timetabling Competition 2007. These are time-assignment models (Stage I of the decomposed model), which are smaller than the full model, but still hard to solve. | 1.383739 | 5 | |
| MIPLIB Top 5 | physiciansched3-3 [MIPLIB] | Pelin Damci-Kurt | Physician scheduling problem for hospitalist, radiology and kidney specialist groups. | 0.809600 | 1 |
| physiciansched5-3 [MIPLIB] | Pelin Damci-Kurt | Physician scheduling problem for hospitalist, radiology and kidney specialist groups. | 1.734424 | 44 | |
| neos-555884 [MIPLIB] | NEOS Server Submission | Imported from the MIPLIB2010 submissions. | 2.004850 | 467 | |
| neos-5193246-nerang [MIPLIB] | Jeff Linderoth | (None provided) | 2.018456 | 516 | |
| neos-5195221-niemur* [MIPLIB] | Jeff Linderoth | (None provided) | 2.018456* | 516* |
physiciansched3-4: Instance-to-Model Comparison Results
| Model Group Assignment from MIPLIB: | physiciansched |
| Assigned Model Group Rank/ISS in the MIC: | 41 / 2.539 |
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 | hypothyroid | bnatt | scp | neos-pseudoapplication-21 | enlight | |
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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 / 1.957 | 2 / 1.995 | 3 / 2.051 | 4 / 2.109 | 5 / 2.142 |
Model Group Summary
The table below contains summary information for the five most similar model groups to physiciansched3-4 according to the MIC.
| MODEL GROUP | SUBMITTER | DESCRIPTION | ISS | RANK | |
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| MIC Top 5 | hypothyroid | Gleb Belov | Linearized Constraint Programming models of the MiniZinc Challenges 2012-2016. I should be able to produce versions with indicator constraints supported by Gurobi and CPLEX, however don't know if you can use them and if there is a standard format. These MPS were produced by Gurobi 7.0.2 using the MiniZinc develop branch on eb536656062ca13325a96b5d0881742c7d0e3c38 | 1.956770 | 1 |
| bnatt | Tatsuya Akutsu | We are submitting ILP data for identification of a singletonattractor in a Boolean newtork, which is a well-known problemin computational systems biology.This problem is known to be NP-hard and we developed a methodto transform an model of the problem to an integer linearprogram (ILP).We used ILPs from artificially generated Boolean networks ofindegree 3.The size of the networks are: 350, 400, 500.Even for the case of 500, we could not find a solution within6 hours using CPLEX 11.2 on a PC with XEON 5470 3.33GHz CPU.(This ILP corresponds to the case of size=350.File format is (zipped) CPLEX LP format.)The details of the method appeared in:T. Akutsu, M. Hayashida and T. Tamura, Integer programming-basedmethods for attractor detection and control of Boolean networks,Proc. The combined 48th IEEE Conference on Decision and Controland 28th Chinese Control Conference (IEEE CDC/CCC 2009), 5610-5617, 2009. | 1.994665 | 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 | 2.051493 | 3 | |
| neos-pseudoapplication-21 | NEOS Server Submission | Imported from the MIPLIB2010 submissions. | 2.108554 | 4 | |
| enlight | A. Zymolka | Model to solve model of a combinatorial game ``EnLight'' Imported from the MIPLIB2010 submissions. | 2.141910 | 5 |
