tanglegram6: Instance-to-Instance Comparison Results

Type: Instance
Submitter: Falk Hueffner
Description: The NP-hard Balanced Subgraph problem (variant of MaxCut) encoded as ILPs. Real-world instances from two applications from bioinformatics, finding monotone subsystems in gene regulatory networks (http://dx.doi.org/10.1007/s10878-009-9212-2) and finding optimal layouts of tanglegrams (http://dx.doi.org/10.1007/978-3-642-11269-0).
MIPLIB Entry

Parent Instance (tanglegram6)

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

tanglegram6 Raw tanglegram6 Decomposed tanglegram6 Composite of MIC top 5 tanglegram6 Composite of MIPLIB top 5 tanglegram6 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.
probportfolio decomposed tanglegram4 decomposed fhnw-schedule-paira100 decomposed fhnw-schedule-paira400 decomposed fhnw-schedule-paira200 decomposed
Name probportfolio [MIPLIB] tanglegram4 [MIPLIB] fhnw-schedule-paira100 [MIPLIB] fhnw-schedule-paira400 [MIPLIB] fhnw-schedule-paira200 [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 / 0.390 2 / 0.447 3 / 0.518 4 / 0.520 5 / 0.532
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIC top 5.
probportfolio raw tanglegram4 raw fhnw-schedule-paira100 raw fhnw-schedule-paira400 raw fhnw-schedule-paira200 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.
tanglegram4 decomposed vpphard2 decomposed vpphard decomposed toll-like decomposed 30_70_45_095_100 decomposed
Name tanglegram4 [MIPLIB] vpphard2 [MIPLIB] vpphard [MIPLIB] toll-like [MIPLIB] 30_70_45_095_100 [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.
2 / 0.447 59 / 0.894 310 / 1.312 343 / 1.349 661 / 1.760
Raw These images represent the CCM images in their raw forms (before any decomposition was applied) for the MIPLIB top 5.
tanglegram4 raw vpphard2 raw vpphard raw toll-like raw 30_70_45_095_100 raw

Instance Summary

The table below contains summary information for tanglegram6, the five most similar instances to tanglegram6 according to the MIC, and the five most similar instances to tanglegram6 according to MIPLIB 2017.

INSTANCE SUBMITTER DESCRIPTION ISS RANK
Parent Instance tanglegram6 [MIPLIB] Falk Hueffner The NP-hard Balanced Subgraph problem (variant of MaxCut) encoded as ILPs. Real-world instances from two applications from bioinformatics, finding monotone subsystems in gene regulatory networks (http://dx.doi.org/10.1007/s10878-009-9212-2) and finding optimal layouts of tanglegrams (http://dx.doi.org/10.1007/978-3-642-11269-0). 0.000000 -
MIC Top 5 probportfolio [MIPLIB] Feng Qiu Sample average approximation formulation of a probabilistic portfolio optimization problem. Solved using ug[SCIP/spx], a distributed massively parallel version of SCIP run on 2,000 cores at the HLRN-II super computer facility. 0.389600 1
tanglegram4 [MIPLIB] Falk Hueffner The NP-hard Balanced Subgraph problem (variant of MaxCut) encoded as ILPs. Real-world instances from two applications from bioinformatics, finding monotone subsystems in gene regulatory networks (http://dx.doi.org/10.1007/s10878-009-9212-2) and finding optimal layouts of tanglegrams (http://dx.doi.org/10.1007/978-3-642-11269-0). 0.447040 2
fhnw-schedule-paira100 [MIPLIB] Simon Felix Continuous-time project scheduling and selection, inspired by an industry use-case. Each project has a value, the sum should be maximized. Each project has a deadline, and an earliest start date. Three formulations of the same problem ("Pair A", "Pair B" and "Slot") - we expect "Pair B" to be the best formulation. 0.518117 3
fhnw-schedule-paira400 [MIPLIB] Simon Felix Continuous-time project scheduling and selection, inspired by an industry use-case. Each project has a value, the sum should be maximized. Each project has a deadline, and an earliest start date. Three formulations of the same problem ("Pair A", "Pair B" and "Slot") - we expect "Pair B" to be the best formulation. 0.520165 4
fhnw-schedule-paira200 [MIPLIB] Simon Felix Continuous-time project scheduling and selection, inspired by an industry use-case. Each project has a value, the sum should be maximized. Each project has a deadline, and an earliest start date. Three formulations of the same problem ("Pair A", "Pair B" and "Slot") - we expect "Pair B" to be the best formulation. 0.531988 5
MIPLIB Top 5 tanglegram4 [MIPLIB] Falk Hueffner The NP-hard Balanced Subgraph problem (variant of MaxCut) encoded as ILPs. Real-world instances from two applications from bioinformatics, finding monotone subsystems in gene regulatory networks (http://dx.doi.org/10.1007/s10878-009-9212-2) and finding optimal layouts of tanglegrams (http://dx.doi.org/10.1007/978-3-642-11269-0). 0.447040 2
vpphard2 [MIPLIB] C. Cardonha Vehicle positioning problem instance. Solved using CPLEX 12.4 in 43987 seconds (May 2012). Solved using Gurobi 5.6.2 in 124 seconds (May 2014).Solved using CPLEX 12.6 in 225 seconds (May 2014). 0.893533 59
vpphard [MIPLIB] C. Cardonha Vehicle positioning problem instance 1.312366 310
toll-like [MIPLIB] Falk Hueffner The NP-hard Balanced Subgraph problem (variant of MaxCut) encoded as ILPs. Real-world instances from two applications from bioinformatics, finding monotone subsystems in gene regulatory networks (http://dx.doi.org/10.1007/s10878-009-9212-2) and finding optimal layouts of tanglegrams (http://dx.doi.org/10.1007/978-3-642-11269-0). Solved by Gurobi 4.6 (8 threads) in about four days after a variable transformation reducing symmetry. 1.349456 343
30_70_45_095_100 [MIPLIB] J. Walser Geographic radar station allocation 1.760329 661


tanglegram6: Instance-to-Model Comparison Results

Model Group Assignment from MIPLIB: huefner
Assigned Model Group Rank/ISS in the MIC: 22 / 1.531

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: map Model group: rmatr Model group: polygonpack Model group: sp_product Model group: neos-pseudoapplication-109
Name map rmatr polygonpack sp_product neos-pseudoapplication-109
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 / 0.799 2 / 0.913 3 / 0.957 4 / 0.977 5 / 1.001

Model Group Summary

The table below contains summary information for the five most similar model groups to tanglegram6 according to the MIC.

MODEL GROUP SUBMITTER DESCRIPTION ISS RANK
MIC Top 5 map Kiyan Ahmadizadeh Land parcel selection problems motivated by Red-Cockaded Woodpecker conservation problem 0.798688 1
rmatr Dmitry Krushinsky Model coming from a formulation of the p-Median problem using square cost matrices 0.913143 2
polygonpack Antonio Frangioni Given a set P of polygons, not necessarily convex, and a rectangle, we want to find the subset S of P with largest possible total area and a position every p in S so that there are no overlaps and they are all included in the rectangle. We allow a small set of rotations (0, 90, 180, 270 degrees) for every polygon. The problem is simplified w.r.t. the real application because the polygons do not have (fully encircled) "holes", which are supposedly filled-in separately, although they can have "bays". Models are saved as .lp. Model LpPackingModel_Dim means that we are trying to pack polygons taken from set ; there are currently 5 different sets, and is 7, 10 or 15. 0.957479 3
sp_product MIPLIB submission pool Imported from the MIPLIB2010 submissions. 0.977167 4
neos-pseudoapplication-109 Jeff Linderoth (None provided) 1.001148 5