1) Design the Objective function for the maximum number of constraints
For simple design, there may be only several variables in my objective
function, and may be hundreds of variables for complicated design. If I fix the
mumber of variables to it's maxium number, it may cause a lot of usless
computation.
2) Fix the non-variable variables using equal upper and lower bounds?
I had try to fix the variable's upper and lower bounds as you say , but it
doesnot work.
//In Visual Studio 2010:
#include "stdafx.h"
#include <math.h>
#include <nlopt.h>
int count = 0;
typedef struct
{
double a, b;
} my_constraint_data;
double myconstraint(unsigned n, const double *x, double *grad, void *data)
{
my_constraint_data *d = (my_constraint_data *) data;
double a = d->a, b = d->b;
if (grad) {
grad[0] = 3 * a * (a*x[0] + b) * (a*x[0] + b);
grad[1] = -1.0;
}
return ((a*x[0] + b) * (a*x[0] + b) * (a*x[0] + b) - x[1]);
}
double myfunc(unsigned n, const double *x, double *grad, void *my_func_data)
{
count++;
printf("eval #%d ",count);
if (grad) {
grad[0] = 0.0;
grad[1] = 0.5 / sqrt(x[1]);
}
printf(" :: f(%f , %f) = %f\n\r",x[0],x[1],sqrt(x[1]));
return sqrt(x[1]);
}
int _tmain(int argc, _TCHAR* argv[])
{
double lb[2] = { -HUGE_VAL, 0.296296};//0 }; /* lower bounds */
double ub[2] = { +HUGE_VAL, 0.296296};//6};
nlopt_opt opt;
opt = nlopt_create(NLOPT_LD_MMA, 2); /* algorithm and dimensionality */
nlopt_set_lower_bounds(opt, lb);
nlopt_set_upper_bounds(opt,ub);
nlopt_set_min_objective(opt, myfunc, NULL);
my_constraint_data data[2] = { {2,0}, {-1,1} };
nlopt_add_inequality_constraint(opt, myconstraint, &data[0], 1e-8);
nlopt_add_inequality_constraint(opt, myconstraint, &data[1], 1e-8);
nlopt_set_xtol_rel(opt, 1e-4);
double x[2] = { 1.234, 0.296296};//5.678 }; /* some initial guess */
double minf; /* the minimum objective value, upon return */
if (nlopt_optimize(opt, x, &minf) < 0) {
printf("nlopt failed!\n");
}
else {
printf("found minimum at f(%g,%g) = %0.10g\n", x[0], x[1], minf);
}
nlopt_destroy(opt);
return 0;
}
I fix the second variable as it's best value: x[2]=0.296296,
The results:
eval #1 :: f(1.234000 , 0.296296) = 0.544331
eval #2 :: f(1.234000 , 1.#QNAN0) = 1.#QNAN0
eval #3 :: f(1.234000 , 1.#QNAN0) = 1.#QNAN0
eval #4 :: f(1.234000 , 1.#QNAN0) = 1.#QNAN0
eval #5 :: f(1.234000 , 1.#QNAN0) = 1.#QNAN0
eval #6 :: f(1.234000 , 1.#QNAN0) = 1.#QNAN0
eval #7 :: f(1.234000 , 1.#QNAN0) = 1.#QNAN0
eval #8 :: f(1.234000 , 1.#QNAN0) = 1.#QNAN0
eval #9 :: f(1.234000 , 1.#QNAN0) = 1.#QNAN0
________________________________
From: "Waters, Anthony" <[email protected]>
To: King Simon <[email protected]>; [email protected]
Sent: Mon, January 17, 2011 6:57:16 PM
Subject: RE: [NLopt-discuss] How to design objective function with
nonconstantnumber of variables?
I’m no expert, but couldn’t you:
1) Design the Objective function for the maximum number of constraints
2) Fix the non-variable variables using equal upper and lower bounds?
__________________________________________________________________________________________
Anthony Waters● Senior Staff Consultant● KBC Process Technology Ltd
T 44 (0)1606 815100● Direct +44 (0)1606 815182● F +44 (0)1606 815151
[email protected]
From:[email protected]
[mailto:[email protected]] On Behalf Of King Simon
Sent: 16 January 2011 10:39
To: [email protected]
Subject: [NLopt-discuss] How to design objective function with
nonconstantnumber
of variables?
Hi,
My objective function have a lot of variables, but the number of variables is
not constant,
for example, the nubmer of varibles is decide by the number of layers of films
every time before optimization.
And some variables may be set to constant value or not, which is decide by the
user,
for example, after several optimazitons, some varible was set to a constant
value. but later, it may be set to varible again.
Is ther anyone meet this kind of problem?
How to design my objective function?
Thanks a lot!
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