Matrix: LPnetlib/lp_ship04l
Description: Netlib LP problem ship04l: minimize c'*x, where Ax=b, lo<=x<=hi
(bipartite graph drawing) |
Matrix properties | |
number of rows | 402 |
number of columns | 2,166 |
nonzeros | 6,380 |
structural full rank? | no |
structural rank | 360 |
# of blocks from dmperm | 6 |
# strongly connected comp. | 43 |
explicit zero entries | 0 |
nonzero pattern symmetry | 0% |
numeric value symmetry | 0% |
type | real |
structure | rectangular |
Cholesky candidate? | no |
positive definite? | no |
author | R. Fourer |
editor | R. Fourer |
date | |
kind | linear programming problem |
2D/3D problem? | no |
Additional fields | size and type |
b | full 402-by-1 |
c | full 2166-by-1 |
lo | full 2166-by-1 |
hi | full 2166-by-1 |
z0 | full 1-by-1 |
Notes:
A Netlib LP problem, in lp/data. For more information send email to netlib@ornl.gov 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 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 SHIP04L 403 2118 8450 57203 1.7933245380E+06 Supplied by Bob Fourer. When included in Netlib: Extra free rows omitted. Source: consulting.
Ordering statistics: | result |
nnz(V) for QR, upper bound nnz(L) for LU, with COLAMD | 47,447 |
nnz(R) for QR, upper bound nnz(U) for LU, with COLAMD | 4,834 |
SVD-based statistics: | |
norm(A) | 13.6375 |
min(svd(A)) | 0 |
cond(A) | Inf |
rank(A) | 360 |
sprank(A)-rank(A) | 0 |
null space dimension | 42 |
full numerical rank? | no |
singular value gap | 1.27247e+13 |
singular values (MAT file): | click here |
SVD method used: | s = svd (full (A)) ; |
status: | ok |
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.