Description: Netlib LP problem ken_07: minimize c'*x, where Ax=b, lo<=x<=hi
|(bipartite graph drawing)|
|number of rows||2,426|
|number of columns||3,602|
|structural full rank?||yes|
|# of blocks from dmperm||990|
|# strongly connected comp.||1|
|explicit zero entries||0|
|nonzero pattern symmetry||0%|
|numeric value symmetry||0%|
|kind||linear programming problem|
|Additional fields||size and type|
A Netlib LP problem, in lp/data/kennington. For more information send email to email@example.com with the message: send index from lp send readme from lp/data send readme from lp/data/kennington The following are relevant excerpts from lp/data/kennington/readme: The "Kennington" problems: sixteen problems described in "An Empirical Evaluation of the KORBX Algorithms for Military Airlift Applications" by W. J. Carolan, J. E. Hill, J. L. Kennington, S. Niemi, S. J. Wichmann (Operations Research vol. 38, no. 2 (1990), pp. 240-248). The following table gives some statistics for the "Kennington" problems. The number of columns excludes slacks and surpluses. The bounds column tells how many entries appear in the BOUNDS section of the MPS file. The mpc column shows the bytes in the problem after "uncompress" and before "emps"; MPS shows the bytes after "emps". The optimal values were computed by Vanderbei's ALPO, running on an SGI computer (with binary IEEE arithmetic). Name rows columns nonzeros bounds mpc MPS optimal value KEN-07 2427 3602 11981 7204 150525 718748 -6.7952044e+08 Submitted to Netlib by Irv Lustig.
|nnz(V) for QR, upper bound nnz(L) for LU, with COLAMD||67,547|
|nnz(R) for QR, upper bound nnz(U) for LU, with COLAMD||15,529|
|null space dimension||49|
|full numerical rank?||no|
|singular value gap||4.57137e+12|
|singular values (MAT file):||click here|
|SVD method used:||s = svd (full (A)) ;|
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.