radiationm18-12-05: Instance-to-Instance Comparison Results

Type: Instance
Submitter: Gleb Belov
Description: 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
MIPLIB Entry

Parent Instance (radiationm18-12-05)

All other instances below were be compared against this "query" instance.

radiationm18-12-05 Raw radiationm18-12-05 Decomposed radiationm18-12-05 Composite of MIC top 5 radiationm18-12-05 Composite of MIPLIB top 5 radiationm18-12-05 Model Group Composite
Raw This is the CCM image before the decomposition procedure has been applied.
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.
Composite of MIC Top 5 Composite of the five decomposed CCM images from the MIC Top 5.
Composite of MIPLIB Top 5 Composite of the five decomposed CCM images from the MIPLIB Top 5.
Model Group Composite Image Composite of the decomposed CCM images for every instance in the same model group as this query.

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.
radiationm40-10-02 decomposed neos-5041756-cobark decomposed neos-4408804-prosna decomposed ns1430538 decomposed neos-824661 decomposed
Name radiationm40-10-02 [MIPLIB] neos-5041756-cobark [MIPLIB] neos-4408804-prosna [MIPLIB] ns1430538 [MIPLIB] neos-824661 [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.
1 / 0.229 2 / 0.238 3 / 0.242 4 / 0.250 5 / 0.253
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIC top 5.
radiationm40-10-02 raw neos-5041756-cobark raw neos-4408804-prosna raw ns1430538 raw neos-824661 raw

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.
radiationm40-10-02 decomposed traininstance6 decomposed supportcase17 decomposed traininstance2 decomposed rocI-3-11 decomposed
Name radiationm40-10-02 [MIPLIB] traininstance6 [MIPLIB] supportcase17 [MIPLIB] traininstance2 [MIPLIB] rocI-3-11 [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.
1 / 0.229 491 / 1.421 499 / 1.431 503 / 1.435 645 / 1.656
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIPLIB top 5.
radiationm40-10-02 raw traininstance6 raw supportcase17 raw traininstance2 raw rocI-3-11 raw

Instance Summary

The table below contains summary information for radiationm18-12-05, the five most similar instances to radiationm18-12-05 according to the MIC, and the five most similar instances to radiationm18-12-05 according to MIPLIB 2017.

INSTANCE SUBMITTER DESCRIPTION ISS RANK
Parent Instance radiationm18-12-05 [MIPLIB] 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 0.000000 -
MIC Top 5 radiationm40-10-02 [MIPLIB] 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 0.229336 1
neos-5041756-cobark [MIPLIB] Jeff Linderoth (None provided) 0.237938 2
neos-4408804-prosna [MIPLIB] Hans Mittelmann Collection of anonymous submissions to the NEOS Server for Optimization 0.242500 3
ns1430538 [MIPLIB] NEOS Server Submission Instance coming from the NEOS Server with unknown application. 0.249779 4
neos-824661 [MIPLIB] NEOS Server Submission Instance coming from the NEOS Server with unknown application 0.252663 5
MIPLIB Top 5 radiationm40-10-02 [MIPLIB] 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 0.229336 1
traininstance6 [MIPLIB] 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 1.421022 491
supportcase17 [MIPLIB] Michael Winkler MIP instances collected from Gurobi forum with unknown application 1.431006 499
traininstance2 [MIPLIB] 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 1.434576 503
rocI-3-11 [MIPLIB] Joerg Rambau Optimal control model in the deterministic dynamic system given by bounded-confidence dynamics in a system of opinions 1.655782 645


radiationm18-12-05: Instance-to-Model Comparison Results

Model Group Assignment from MIPLIB: radiation
Assigned Model Group Rank/ISS in the MIC: 1 / 0.255

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.
Model group: radiation Model group: n37 Model group: seqsolve Model group: graphs Model group: sp_product
Name radiation n37 seqsolve graphs sp_product
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.
1 / 0.256 2 / 0.335 3 / 0.587 4 / 0.670 5 / 0.672

Model Group Summary

The table below contains summary information for the five most similar model groups to radiationm18-12-05 according to the MIC.

MODEL GROUP SUBMITTER DESCRIPTION ISS RANK
MIC Top 5 radiation 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 0.255580 1
n37 J. Aronson Fixed charge transportation problem 0.334862 2
seqsolve Irv Lustig The 3 problems in this group (seqsolve1-seqsolve3) represent a hierarchical optimization process, which is derived from a customer problem for assigning people to sites into blocks of time on days of the week. The specialty of this submission is that the best known solution for seqsolveX can be used as a MIP start for seqsolveX+1. For a description of the connections between the problems, please refer to the README.txt contained in the model data for this submission, which also includes MIP start files and a Gurobi log file. 0.586950 3
graphs Michael Bastubbe Packing Cuts in Undirected Graphs. Models are described in 4.1. 0.669948 4
sp_product MIPLIB submission pool Imported from the MIPLIB2010 submissions. 0.672416 5


Updated August 16, 2019