Geometric Presolver example
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The most logical strategy is to make the problem smaller. | The most logical strategy is to make the problem smaller. | ||
| - | This file contains a real E matrix having dimension <math>533\times 2704</math> and compatible <math>t</math> vector. There exists a cardinality <math>36</math> binary solution <math>x</math>. Before attempting to find it, we presume to have no choice but to reduce dimension of the <math>E</math> matrix prior to computing a solution. | + | [http://www.convexoptimization.com/TOOLS/EAndy.mat This Matlab workspace file] |
| + | contains a real <math>E</math> matrix having dimension <math>533\times 2704</math> and compatible <math>t</math> vector. There exists a cardinality <math>36</math> binary solution <math>x</math>. Before attempting to find it, we presume to have no choice but to reduce dimension of the <math>E</math> matrix prior to computing a solution. | ||
A lower bound on the number of rows of <math>\,E\in\mathbb{R}^{533\times 2704}\,</math> retained is <math>217</math>.<br> | A lower bound on the number of rows of <math>\,E\in\mathbb{R}^{533\times 2704}\,</math> retained is <math>217</math>.<br> | ||
Revision as of 16:54, 11 April 2013
Assume that the following problem is massive:
The problem is presumed solvable but not computable by any contemporary means. The most logical strategy is to make the problem smaller.
This Matlab workspace file
contains a real matrix having dimension
and compatible
vector. There exists a cardinality
binary solution
. Before attempting to find it, we presume to have no choice but to reduce dimension of the
matrix prior to computing a solution.
A lower bound on the number of rows of retained is
.
A lower bound on the number of columns retained is .
The present exercise is to determine those rows and columns using any contemporary presolver.