pal.math
Class ConjugateDirectionSearch
java.lang.Object
|
+--pal.math.MultivariateMinimum
|
+--pal.math.ConjugateDirectionSearch
- public class ConjugateDirectionSearch
- extends MultivariateMinimum
methods for minimization of a real-valued function of
several variables without using derivatives (Brent's modification
of a conjugate direction search method proposed by Powell)
Field Summary |
boolean |
illc
illc should be set to true
if the problem is known to
be ill-conditioned. the default is false. this
variable is automatically set, when the problem
is found to to be ill-conditioned during iterations. |
int |
prin
controls the printed output from the routine
(0 -> no output, 1 -> print only starting and final values,
2 -> detailed map of the minimization process,
3 -> print also eigenvalues and vectors of the
search directions), the default value is 0 |
double |
scbd
scbd is a scaling parameter. 1.0 is the default and
indicates no scaling. if the scales for the different
parameters are very different, scbd should be set to
a value of about 10.0. |
double |
step
step is a steplength parameter and should be set equal
to the expected distance from the solution.
exceptionally small or large values of step lead to
slower convergence on the first few iterations
the default value for step is 1.0 |
Method Summary |
void |
optimize(MultivariateFunction f,
double[] xvector,
double tolfx,
double tolx)
The actual optimization routine
(needs to be implemented in a subclass of MultivariateMinimum).
|
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
prin
public int prin
- controls the printed output from the routine
(0 -> no output, 1 -> print only starting and final values,
2 -> detailed map of the minimization process,
3 -> print also eigenvalues and vectors of the
search directions), the default value is 0
step
public double step
- step is a steplength parameter and should be set equal
to the expected distance from the solution.
exceptionally small or large values of step lead to
slower convergence on the first few iterations
the default value for step is 1.0
scbd
public double scbd
- scbd is a scaling parameter. 1.0 is the default and
indicates no scaling. if the scales for the different
parameters are very different, scbd should be set to
a value of about 10.0.
illc
public boolean illc
- illc should be set to true
if the problem is known to
be ill-conditioned. the default is false. this
variable is automatically set, when the problem
is found to to be ill-conditioned during iterations.
ConjugateDirectionSearch
public ConjugateDirectionSearch()
- constructor
optimize
public void optimize(MultivariateFunction f,
double[] xvector,
double tolfx,
double tolx)
- Description copied from class:
MultivariateMinimum
- The actual optimization routine
(needs to be implemented in a subclass of MultivariateMinimum).
It finds a minimum close to vector x when the
absolute tolerance for each parameter is specified.
- Overrides:
optimize
in class MultivariateMinimum
- Following copied from class:
pal.math.MultivariateMinimum
- Parameters:
f
- multivariate functionxvec
- initial guesses for the minimum
(contains the location of the minimum on return)tolfx
- absolute tolerance of function valuetolx
- absolute tolerance of each parameter