Matrix: LPnetlib/lpi_itest6

Description: Netlib LP problem itest6: minimize c'*x, where Ax=b, lo<=x<=hi

LPnetlib/lpi_itest6 graph
(bipartite graph drawing)


LPnetlib/lpi_itest6
scc of LPnetlib/lpi_itest6

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  • download as a MATLAB mat-file, file size: 2 KB. Use UFget(720) or UFget('LPnetlib/lpi_itest6') in MATLAB.
  • download in Matrix Market format, file size: 1 KB.
  • download in Rutherford/Boeing format, file size: 2 KB.

    Matrix properties
    number of rows11
    number of columns17
    nonzeros29
    structural full rank?yes
    structural rank11
    # of blocks from dmperm1
    # strongly connected comp.3
    explicit zero entries0
    nonzero pattern symmetry 0%
    numeric value symmetry 0%
    typereal
    structurerectangular
    Cholesky candidate?no
    positive definite?no

    authorJ. Chinneck, E. Dravnieks
    editorJ. Chinneck
    date1991
    kindlinear programming problem
    2D/3D problem?no

    Additional fieldssize and type
    bfull 11-by-1
    cfull 17-by-1
    lofull 17-by-1
    hifull 17-by-1
    z0full 1-by-1

    Notes:

    An infeasible Netlib LP problem, in lp/infeas.  For more information        
    send email to netlib@ornl.gov with the message:                             
                                                                                
    	send index from lp                                                         
    	send readme from lp/infeas                                                 
                                                                                
    The lp/infeas directory contains infeasible linear programming test problems
    collected by John W. Chinneck, Carleton Univ, Ontario Canada.  The following
    are relevant excerpts from lp/infeas/readme (by John W. Chinneck):          
                                                                                
    In the following, IIS stands for Irreducible Infeasible Subsystem, a set    
    of constraints which is itself infeasible, but becomes feasible when any    
    one member is removed.  Isolating an IIS from within the larger set of      
    constraints defining the model is one analysis approach.                    
                                                                                
    PROBLEM DESCRIPTION                                                         
    -------------------                                                         
                                                                                
    ITEST6, ITEST2:  very small problems having numerous clustered IISs.        
    These match problems 1 and 2, respectively, in Chinneck and Dravnieks       
    [1991].  Contributors:  J.W.  Chinneck and E.W.  Dravnieks, Carleton        
    University.                                                                 
                                                                                
    Name       Rows   Cols   Nonzeros Bounds      Notes                         
    itest6       12      8       23                                             
                                                                                
    REFERENCES                                                                  
    ----------                                                                  
                                                                                
    J.W.  Chinneck and E.W.  Dravnieks (1991).  "Locating Minimal Infeasible    
    Constraint Sets in Linear Programs", ORSA Journal on Computing, Volume      
    3, No. 2.                                                                   
                                                                                
    

    Ordering statistics:result
    nnz(V) for QR, upper bound nnz(L) for LU, with COLAMD30
    nnz(R) for QR, upper bound nnz(U) for LU, with COLAMD32

    SVD-based statistics:
    norm(A)3.35268
    min(svd(A))0.0223111
    cond(A)150.27
    rank(A)11
    sprank(A)-rank(A)0
    null space dimension0
    full numerical rank?yes

    singular values (MAT file):click here
    SVD method used:s = svd (full (R)) ; where [~,R,E] = spqr (A') with droptol of zero
    status:ok

    LPnetlib/lpi_itest6 svd

    For a description of the statistics displayed above, click here.

    Maintained by Tim Davis, last updated 12-Mar-2014.
    Matrix pictures by cspy, a MATLAB function in the CSparse package.
    Matrix graphs by Yifan Hu, AT&T Labs Visualization Group.