FMINSEARCHBND: FMINSEARCH, but with bound constraints by transformation
usage: x=FMINSEARCHBND(fun,x0)
usage: x=FMINSEARCHBND(fun,x0,LB)
usage: x=FMINSEARCHBND(fun,x0,LB,UB)
usage: x=FMINSEARCHBND(fun,x0,LB,UB,options)
usage: x=FMINSEARCHBND(fun,x0,LB,UB,options,p1,p2,...)
usage: [x,fval,exitflag,output]=FMINSEARCHBND(fun,x0,...)
arguments:
fun, x0, options - see the help for FMINSEARCH
LB - lower bound vector or array, must be the same size as x0
If no lower bounds exist for one of the variables, then
supply -inf for that variable.
If no lower bounds at all, then LB may be left empty.
Variables may be fixed in value by setting the corresponding
lower and upper bounds to exactly the same value.
UB - upper bound vector or array, must be the same size as x0
If no upper bounds exist for one of the variables, then
supply +inf for that variable.
If no upper bounds at all, then UB may be left empty.
Variables may be fixed in value by setting the corresponding
lower and upper bounds to exactly the same value.
Notes:
If options is supplied, then TolX will apply to the transformed
variables. All other FMINSEARCH parameters should be unaffected.
Variables which are constrained by both a lower and an upper
bound will use a sin transformation. Those constrained by
only a lower or an upper bound will use a quadratic
transformation, and unconstrained variables will be left alone.
Variables may be fixed by setting their respective bounds equal.
In this case, the problem will be reduced in size for FMINSEARCH.
The bounds are inclusive inequalities, which admit the
boundary values themselves, but will not permit ANY function
evaluations outside the bounds. These constraints are strictly
followed.
If your problem has an EXCLUSIVE (strict) constraint which will
not admit evaluation at the bound itself, then you must provide
a slightly offset bound. An example of this is a function which
contains the log of one of its parameters. If you constrain the
variable to have a lower bound of zero, then FMINSEARCHBND may
try to evaluate the function exactly at zero.
Example usage:
rosen = @(x) (1-x(1)).^2 + 105*(x(2)-x(1).^2).^2;
fminsearch(rosen,[3 3]) % unconstrained
ans =
1.0000 1.0000
fminsearchbnd(rosen,[3 3],[2 2],[]) % constrained
ans =
2.0000 4.0000
See test_main.m for other examples of use.
See also: fminsearch, fminspleas
Author: John D'Errico
E-mail: woodchips@rochester.rr.com
Release: 4
Release date: 7/23/06