Matrix: LPnetlib/lp_sc105
Description: Netlib LP problem sc105: minimize c'*x, where Ax=b, lo<=x<=hi
(bipartite graph drawing) |
Matrix properties | |
number of rows | 105 |
number of columns | 163 |
nonzeros | 340 |
structural full rank? | yes |
structural rank | 105 |
# of blocks from dmperm | 2 |
# strongly connected comp. | 2 |
explicit zero entries | 0 |
nonzero pattern symmetry | 0% |
numeric value symmetry | 0% |
type | real |
structure | rectangular |
Cholesky candidate? | no |
positive definite? | no |
author | N. Gould |
editor | D. Gay |
date | 1989 |
kind | linear programming problem |
2D/3D problem? | no |
Additional fields | size and type |
b | full 105-by-1 |
c | full 163-by-1 |
lo | full 163-by-1 |
hi | full 163-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 SC105 106 103 281 3307 -5.2202061212E+01 Nick Gould supplied SC105 from the Harwell collection of LP test problems. When included in Netlib: Cost coefficients negated. Added to Netlib on 6 April 1989
Ordering statistics: | result |
nnz(V) for QR, upper bound nnz(L) for LU, with COLAMD | 1,751 |
nnz(R) for QR, upper bound nnz(U) for LU, with COLAMD | 573 |
SVD-based statistics: | |
norm(A) | 4.09956 |
min(svd(A)) | 0.111386 |
cond(A) | 36.8048 |
rank(A) | 105 |
sprank(A)-rank(A) | 0 |
null space dimension | 0 |
full numerical rank? | yes |
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.