Matrix: LPnetlib/lpi_cplex1

Description: Netlib LP problem cplex1: minimize c'*x, where Ax=b, lo<=x<=hi

LPnetlib/lpi_cplex1 graph
(bipartite graph drawing)


LPnetlib/lpi_cplex1

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  • Matrix group: LPnetlib
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  • download as a MATLAB mat-file, file size: 46 KB. Use UFget(710) or UFget('LPnetlib/lpi_cplex1') in MATLAB.
  • download in Matrix Market format, file size: 60 KB.
  • download in Rutherford/Boeing format, file size: 52 KB.

    Matrix properties
    number of rows3,005
    number of columns5,224
    nonzeros10,947
    structural full rank?yes
    structural rank3,005
    # of blocks from dmperm1
    # strongly connected comp.1
    explicit zero entries0
    nonzero pattern symmetry 0%
    numeric value symmetry 0%
    typereal
    structurerectangular
    Cholesky candidate?no
    positive definite?no

    authorE. Klotz
    editorJ. Chinneck
    date1993
    kindlinear programming problem
    2D/3D problem?no

    Additional fieldssize and type
    bfull 3005-by-1
    cfull 5224-by-1
    lofull 5224-by-1
    hifull 5224-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                                                         
    -------------------                                                         
                                                                                
    CPLEX1, CPLEX2:  medium and large problems respectively.  CPLEX1            
    referred to as CPLEX problem in Chinneck [1993], and is remarkably          
    non-volatile, showing a single small IIS regardless of the IIS algorithm    
    applied.  CPLEX2 is an almost-feasible problem. Contributor:  Ed Klotz,     
    CPLEX Optimization Inc.                                                     
                                                                                
    Name       Rows   Cols   Nonzeros Bounds      Notes                         
    cplex1     3006   3221    10664   B            dense col (> 1500)           
                                                                                
    REFERENCES                                                                  
    ----------                                                                  
                                                                                
    J.W.  Chinneck (1993).  "Finding the Most Useful Subset of Constraints      
    for Analysis in an Infeasible Linear Program", technical report             
    SCE-93-07, Systems and Computer Engineering, Carleton University,           
    Ottawa, Canada.                                                             
                                                                                
    

    Ordering statistics:result
    nnz(V) for QR, upper bound nnz(L) for LU, with COLAMD2,232,799
    nnz(R) for QR, upper bound nnz(U) for LU, with COLAMD1,514,006

    SVD-based statistics:
    norm(A)200.007
    min(svd(A))0.0638664
    cond(A)3131.64
    rank(A)3,005
    sprank(A)-rank(A)0
    null space dimension0
    full numerical rank?yes

    singular values (MAT file):click here
    SVD method used:s = svd (full (A)) ;
    status:ok

    LPnetlib/lpi_cplex1 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.