Submitter Variables Constraints Density Status Group Objective MPS File
Tatsuya Akutsu 4500 7029 8.60024e-04 hard bnatt Infeasible bnatt500.mps.gz

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 instance 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.

Imported from the MIPLIB2010 submissions.

Instance Statistics

Detailed explanation of the following tables can be found here.

Size Related Properties
Original Presolved
Variables 4500 2529
Constraints 7029 5058
Binaries 4500 2529
Integers 0 0
Continuous 0 0
Implicit Integers 0 0
Fixed Variables 0 0
Nonzero Density 0.000860024 0.001664360
Nonzeroes 27203 21290
Constraint Classification Properties
Original Presolved
Total 7029 5058
Empty 0 0
Free 0 0
Singleton 1971 0
Aggregations 0 0
Precedence 0 24
Variable Bound 0 0
Set Partitioning 0 0
Set Packing 0 0
Set Covering 2029 260
Cardinality 0 0
Invariant Knapsack 500 2257
Equation Knapsack 0 0
Bin Packing 0 488
Knapsack 0 2029
Integer Knapsack 0 0
Mixed Binary 2529 0
General Linear 0 0
Indicator 0 0

Structure

Available nonzero structure and decomposition information. Further information can be found here.

value min median mean max
Components 2.589950
Constraint % 0.0395413 0.0395413 0.0395413 0.0395413
Variable % 0.0790826 0.2120760 0.1977070 0.3558720
Score 0.153095

Best Known Solution(s)

No solution available for bnatt500 .

Similar instances in collection

The following instances are most similar to bnatt500 in the collection. This similarity analysis is based on 100 scaled instance features describing properties of the variables, objective function, bounds, constraints, and right hand sides.

Instance Variables Binaries Integers Continuous Constraints Nonz. Submitter Group Status Objective
bnatt400 3600 3600 0 0 5614 21698 Tatsuya Akutsu bnatt easy 1
s1234 2945 2945 0 0 8418 44641 Siwei Sun SiweiSun open 34*
neos-5178119-nalagi 4167 4068 0 99 6921 74476 Jeff Linderoth neos-pseudoapplication-62 easy 22.73999999763
circ10-3 2700 2700 0 0 42620 307320 M. Winkler open 378*
supportcase3 4191 4191 0 0 12702 53470 Michael Winkler hard 0

Reference

No bibliographic information available

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