swath1: Instance-to-Instance Comparison Results

Type: Instance
Submitter: D. Panton
Description: Model arising from the defense industry, involves planning missions for radar surveillance.
MIPLIB Entry

Parent Instance (swath1)

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

swath1 Raw swath1 Decomposed swath1 Composite of MIC top 5 swath1 Composite of MIPLIB top 5 swath1 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.
swath2 decomposed swath3 decomposed swath decomposed mad decomposed ger50-17-ptp-pop-6t decomposed
Name swath2 [MIPLIB] swath3 [MIPLIB] swath [MIPLIB] mad [MIPLIB] ger50-17-ptp-pop-6t [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 / 0.438 2 / 0.799 3 / 1.202 4 / 1.427 5 / 1.469
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIC top 5.
swath2 raw swath3 raw swath raw mad raw ger50-17-ptp-pop-6t 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.
swath2 decomposed swath3 decomposed swath decomposed neos-5221106-oparau decomposed ns2071214 decomposed
Name swath2 [MIPLIB] swath3 [MIPLIB] swath [MIPLIB] neos-5221106-oparau [MIPLIB] ns2071214 [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 / 0.438 2 / 0.799 3 / 1.202 390 / 1.920 462 / 1.945
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIPLIB top 5.
swath2 raw swath3 raw swath raw neos-5221106-oparau raw ns2071214 raw

Instance Summary

The table below contains summary information for swath1, the five most similar instances to swath1 according to the MIC, and the five most similar instances to swath1 according to MIPLIB 2017.

INSTANCE SUBMITTER DESCRIPTION ISS RANK
Parent Instance swath1 [MIPLIB] D. Panton Model arising from the defense industry, involves planning missions for radar surveillance. 0.000000 -
MIC Top 5 swath2 [MIPLIB] D. Panton Model arising from the defense industry, involves planning missions for radar surveillance. 0.438104 1
swath3 [MIPLIB] D. Panton Model arising from the defense industry, involves planning missions for radar surveillance. 0.798517 2
swath [MIPLIB] D. Panton Model arising from the defense industry, involves planning missions for radar surveillance. John Forrest and Laszlo Ladanyi solved this instance by reformulation in 1999. Alkis Vazacopoulos reports solving this instance using XPRESS 2006B. 1.202000 3
mad [MIPLIB] Koichi Fujii Mean-Absolute Deviation Model for Car Dealerships 1.426791 4
ger50-17-ptp-pop-6t [MIPLIB] C. Raack Multi-layer network design problem using a link-flow formulation over a path-flow formulation. 1.468598 5
MIPLIB Top 5 swath2 [MIPLIB] D. Panton Model arising from the defense industry, involves planning missions for radar surveillance. 0.438104 1
swath3 [MIPLIB] D. Panton Model arising from the defense industry, involves planning missions for radar surveillance. 0.798517 2
swath [MIPLIB] D. Panton Model arising from the defense industry, involves planning missions for radar surveillance. John Forrest and Laszlo Ladanyi solved this instance by reformulation in 1999. Alkis Vazacopoulos reports solving this instance using XPRESS 2006B. 1.202000 3
neos-5221106-oparau [MIPLIB] Hans Mittelmann Seem to be VRP output from 2-hour runs of Gurobi on 12 threads is included 1.920037 390
ns2071214 [MIPLIB] NEOS Server Submission Imported from the MIPLIB2010 submissions. 1.945279 462


swath1: Instance-to-Model Comparison Results

Model Group Assignment from MIPLIB: swath
Assigned Model Group Rank/ISS in the MIC: 1 / 1.360

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: swath Model group: scp Model group: neos-pseudoapplication-21 Model group: timtab Model group: stein
Name swath scp neos-pseudoapplication-21 timtab stein
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 / 1.360 2 / 1.726 3 / 1.888 4 / 1.925 5 / 1.997

Model Group Summary

The table below contains summary information for the five most similar model groups to swath1 according to the MIC.

MODEL GROUP SUBMITTER DESCRIPTION ISS RANK
MIC Top 5 swath D. Panton Model arising from the defense industry, involves planning missions for radar surveillance. John Forrest and Laszlo Ladanyi solved this model by reformulation in 1999. Alkis Vazacopoulos reports solving this model using XPRESS 2006B. 1.360225 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 1.726032 2
neos-pseudoapplication-21 NEOS Server Submission Imported from the MIPLIB2010 submissions. 1.888029 3
timtab C. Liebchen, R. Möhring Public transport scheduling problem 1.925087 4
stein MIPLIB submission pool Imported from the MIPLIB2010 submissions. 1.997075 5


Updated August 16, 2019