/* We illustrate the operation of the code using the problem        min \sum_{i=1}^n  exp (x [i]) - sqrt (i)*x [i] ;        subject to 0 <= x <= 1   We solve the problem 3 times using different parameter setting.   On a linux workstation, the final statistics generated by driver1   were as follows:Final convergence status = 0Convergence tolerance for gradient satisfiedabsolute largest component of projected gradient: 5.642870e-09function value:               -4.0110349e+02Total cg  iterations:                    8Total cg  function evaluations:         13Total cg  gradient evaluations:         13Total cbb iterations:                    5Total cbb function evaluations:          6Total cbb gradient evaluations:          6------------------------------------------Total function evaluations:             19Total gradient evaluations:             19==========================================See the drivers in the distribution of cg_descent Version 3.0for more examples */#include <math.h> #include "asa_user.h" /* needed by the program which calls asa_cg *//* prototypes for the function and gradient evaluation routines */double myvalue(double *x, INT n) ;void mygrad(double  *g, double  *x, INT n) ;double myvalgrad(double  *g, double  *x, INT n) ;int main (void){    double *x, *lo, *hi ;	double grad_tol;    INT i, n ;    /* if you want to change parameter value, you need the following: */    asacg_parm cgParm ;    asa_parm asaParm ;	/* tolerance */	grad_tol = 1.e-8;    /* allocate arrays for problem solution and bounds */    n = 100 ; /* problem dimension */    x  = (double *) malloc (n*sizeof (double)) ;    lo = (double *) malloc (n*sizeof (double)) ;    hi = (double *) malloc (n*sizeof (double)) ;    for (i = 0; i < n; i++) lo [i] = (double) 0 ;    for (i = 0; i < n; i++) hi [i] = (double) 1 ;    /* if you want to change parameter value, initialize strucs with default */    asa_cg_default (&cgParm) ;    asa_default (&asaParm) ;    /* if you want to change parameters, change them here: */    cgParm.PrintParms = TRUE ;    cgParm.PrintLevel = 1 ;    asaParm.PrintParms = TRUE ;    asaParm.PrintLevel = 1 ;    ///* starting guess */    //for (i = 0; i < n; i++) x[i] = 1 ;    ///* run the code */    //asa_cg (x, lo, hi, n, NULL, &cgParm, &asaParm, grad_tol, myvalue, mygrad, myvalgrad, NULL) ;    /* if no change in parameters, you could replace Parm arguments by NULL*/	/* starting guess */    //for (i = 0; i < n; i++) x [i] = 1 ;    //asa_cg (x, lo, hi, n, NULL, NULL, NULL, grad_tol, myvalue, mygrad, myvalgrad, NULL) ; //   /* with some loss of efficiency, you could omit the valgrad routine */	/* starting guess */	for (i = 0; i < n; i++) x [i] = 1 ;      asa_cg (x, lo, hi, n, NULL, NULL, NULL, grad_tol, myvalue, mygrad, NULL, NULL);    free (x) ;    free (lo) ;    free (hi) ;}/* evaluate the objective function */double myvalue(double *x, INT n){    double f, t ;    INT i ;    f = 0. ;    for (i = 0; i < n; i++)    {        t = i + 1 ;        t = sqrt (t) ;        f += exp (x [i]) - t*x [i] ;    }    return (f) ;}/* evaluate the gradient of the objective function */void mygrad(double  *g, double  *x, INT n){    double t ;    INT i ;    for (i = 0; i < n; i++)    {        t = i + 1 ;        t = sqrt (t) ;        g [i] = exp (x [i]) -  t ;    }    return ;}/* value and gradient of the objective function */double myvalgrad (double  *g, double  *x, INT n){    double f, xi, t ;    INT i ;    f = 0 ;    for (i = 0; i < n; i++)    {        t = i + 1 ;        t = sqrt (t) ;        xi = x [i] ;        f += exp (xi) - t*xi ;        g [i] = exp (xi) -  t ;    }    return (f) ;}