get_scaling
Specifies which scaling algorithm is used.
int get_scaling(lprec *lp);
Return Value
get_scaling returns which scaling algorithm is used. Can by any of the
following values:
SCALE_EXTREME (1) |
Scale to convergence using largest absolute value |
SCALE_RANGE (2) |
Scale based on the simple numerical range |
SCALE_MEAN (3) |
Numerical range-based scaling |
SCALE_GEOMETRIC (4) |
Geometric scaling |
SCALE_CURTISREID (7) |
Curtis-reid scaling |
Additionally, the value can be OR-ed with any combination of one of the
following values:
SCALE_QUADRATIC (8) |
|
SCALE_LOGARITHMIC (16) |
Scale to convergence using logarithmic mean of all values |
SCALE_USERWEIGHT (31) |
User can specify scalars |
SCALE_POWER2 (32) |
also do Power scaling |
SCALE_EQUILIBRATE (64) |
Make sure that no scaled number is above 1 |
SCALE_INTEGERS (128) |
also scaling integer variables |
SCALE_DYNUPDATE (256) |
dynamic update |
Parameters
lp
Pointer to previously created lp model. See return value of
make_lp, read_lp,
read_LP, read_mps, read_freemps, read_MPS, read_freeMPS, read_XLI
Remarks
The get_scaling function returns which scaling algorithm is used. This
can influence numerical stability considerably. It is advisable to always use
some sort of scaling.
set_scaling must be called before
solve is called.
SCALE_EXTREME, SCALE_RANGE, SCALE_MEAN, SCALE_GEOMETRIC, SCALE_CURTISREID are
the possible scaling algorithms. SCALE_QUADRATIC, SCALE_LOGARITHMIC,
SCALE_USERWEIGHT, SCALE_POWER2, SCALE_EQUILIBRATE, SCALE_INTEGERS are possible
additional scaling parameters.
SCALE_POWER2 results in creating a scalar of power 2. May improve stability.
SCALE_INTEGERS results also in scaling Integer columns. Default they are not
scaled.
SCALE_DYNUPDATE is new from version 5.1.1.0
It has always been so that scaling is done only once on the original model. If a solve
is done again (most probably after changing some data in the model), the scaling factors
aren't computed again. The scalars of the original model are used. This is not always
good, especially if the data has changed considerably. One way to solve this was/is call
unscale before a next solve. In that case, scale factors are recomputed.
From version 5.1.1.0 on, there is another
way to make sure that scaling factors are recomputed and this is by settings SCALE_DYNUPDATE. In
that case, the scaling factors are recomputed also when a restart is done. Note
that they are then always recalculated with each solve, even when no change was made to the model, or
a change that doesn't influence the scaling factors like changing the RHS (Right Hand Side) values
or the bounds/ranges. This can influence performance. It is up to you to decide
if scaling factors must be recomputed or not for a new solve, but by default it still isn't so.
It is possible to set/unset this flag at each next solve and it is even allowed to choose
a new scaling algorithm between each solve. Note that the scaling done by the SCALE_DYNUPDATE is incremental
and the resulting scalars are typically different from scalars recomputed from scratch.
Example
#include <stdio.h>
#include <stdlib.h>
#include "lp_lib.h"
int main(void)
{
lprec *lp;
int scalemode;
/* Create a new LP model */
lp = make_lp(0, 0);
if(lp == NULL) {
fprintf(stderr, "Unable to create new LP model\n");
return(1);
}
scalemode = get_scaling(lp); /* Will return 0 */
delete_lp(lp);
return(0);
}
lp_solve API reference
See Also make_lp,
read_lp, read_LP, read_mps,
read_freemps, read_MPS, read_freeMPS, read_XLI, set_scaling,
set_scalelimit, get_scalelimit, is_integerscaling, is_scalemode, is_scaletype
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