Description: Netlib LP problem fit2p: minimize c'*x, where Ax=b, lo<=x<=hi
|(bipartite graph drawing)|
|number of rows||3,000|
|number of columns||13,525|
|structural full rank?||yes|
|# of blocks from dmperm||1|
|# 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. For more information send email to email@example.com with the message: send index from lp send readme from lp/data The following are relevant excerpts from lp/data/readme (by David M. Gay): The column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude slack and surplus columns and the right-hand side vector, but include the cost row. We have omitted other free rows and all but the first right-hand side vector, as noted below. The byte count is for the MPS compressed file; it includes a newline character at the end of each line. These files start with a blank initial line intended to prevent mail programs from discarding any of the data. The BR column indicates whether a problem has bounds or ranges: B stands for "has bounds", R for "has ranges". The BOUND-TYPE TABLE below shows the bound types present in those problems that have bounds. The optimal value is from MINOS version 5.3 (of Sept. 1988) running on a VAX with default options. PROBLEM SUMMARY TABLE Name Rows Cols Nonzeros Bytes BR Optimal Value FIT2P 3001 13525 60784 439794 B 6.8464293232E+04 BOUND-TYPE TABLE FIT2P UP Supplied by Bob Fourer. Concerning FIT1D, FIT1P, FIT2D, FIT2P, Bob Fourer says The pairs FIT1P/FIT1D and FIT2P/FIT2D are primal and dual versions of the same two problems [except that we have negated the cost coefficients of the dual problems so all are minimization problems]. They originate from a model for fitting linear inequalities to data, by minimization of a sum of piecewise-linear penalties. The FIT1 problems are based on 627 data points and 2-3 pieces per primal pl penalty term. The FIT2 problems are based on 3000 data points (from a different sample altogether) and 4-5 pieces per pl term. Added to Netlib on 31 Jan. 1990
|nnz(V) for QR, upper bound nnz(L) for LU, with COLAMD||14,846,550|
|nnz(R) for QR, upper bound nnz(U) for LU, with COLAMD||4,501,500|
|null space dimension||0|
|full numerical rank?||yes|
|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.