bool eval_x ( Eval_Point & x ,
const Double & h_max ,
bool & count_eval ) const {
int n = x.size();
int m = x.get_bb_outputs().size();
int i;
double * xx = new double [n];
double * fx = new double [m];
for ( i = 0 ; i < x.size() ; ++i )
xx[i] = x[i].value();
// call the FORTRAN routine:
bb_ ( xx , fx );
for ( i = 0 ; i < m ; ++i )
x.set_bb_output ( i , fx[i] );
count_eval = true; // count a black-box evaluation
return true; // the evaluation succeeded
}
bool eval_x ( Eval_Point & x ,
const Double & h_max ,
bool & count_eval ) const {
Double c1 = 0.0 , c2 = 0.0;
for ( int i = 0 ; i < 5 ; i++ ) {
c1 += (x[i]-1).pow2();
c2 += (x[i]+1).pow2();
}
x.set_bb_output ( 0 , x[4] ); // objective 1
x.set_bb_output ( 1 , c1-25 ); // objective 2
x.set_bb_output ( 2 , 25-c2 ); // constraint 1
count_eval = true; // count a black-box evaluation
return true; // the evaluation succeeded
}
bool eval_x ( Eval_Point & x ,
const Double & h_max ,
bool & count_eval ) const {
double xx[42];
double fx[1];
int i;
// cout << "eval_x: values of x\n";
for ( i = 0 ; i < 42 ; ++i ) {
xx[i] = x[i].value();
// cout << i << " " << xx[i] << "\n" ;
}
// call the FORTRAN routine:
// cout << "Calling bb_kleed\n";
bb_kleed_ ( xx , fx );
for ( i = 0 ; i < 1 ; ++i )
x.set_bb_output ( i , fx[i] );
count_eval = true; // count a black-box evaluation
return true; // the evaluation succeeded
}
// eval_x:
bool My_Evaluator::eval_x ( Eval_Point & ep ,
const Double & h_max ,
bool & count_eval ) const {
count_eval = true;
int epi = 0;
_x[0] = ep[epi++].value(); _y[0] = 0.0;
_x[1] = ep[epi++].value(); _y[1] = 0.0;
_y[2] = ep[epi++].value(); _x[2] = 0.0;
_x[3] = ep[epi++].value();
_y[3] = ep[epi++].value();
int ic = 0 , i , j;
double constraint = 0.0;
for ( i = 4 ; i < _NBC ; ++i ) {
_x[i] = ep[epi++].value();
_y[i] = ep[epi++].value();
}
ep.set_bb_output ( ic++ , constraint );
double dist , distmax = 0.0, avg_dist = 0.0;
constraint = 1.0;
/*for ( i = 0 ; i < _NBC ; ++i ) {
for( j = i+1 ; j < _NBC ; ++j ) {
dist = pow(_x[i]-_x[j],2) + pow(_y[i]-_y[j],2);
avg_dist += sqrt(dist);
if ( dist > distmax )
distmax = dist;
if( dist < 1 ) constraint *= dist;
}
}
ep.set_bb_output ( ic++ , 1.0-constraint );
ep.set_bb_output ( _M , sqrt(distmax) );
*/
for ( i = 0 ; i < _NBC-1 ; ++i ) {
// out << " ( "<< _x[i] << ", " << _y[i] << " ) \n";
for( j = i+1 ; j < _NBC ; ++j ) {
dist = pow(_x[i]-_x[j],2) + pow(_y[i]-_y[j],2);
if ( dist > distmax )
distmax = dist;
if( dist < 1 ) {
constraint *= sqrt(dist);
}
else if( dist > 14)
avg_dist += sqrt(dist);
// out << i << " " << j << " . " << sqrt(dist) << endl;
}
}
// out << distmax << " " << avg_dist << " " << constraint << " ";
if (constraint < 0.9999)
constraint = 1001.0-constraint;
else
constraint = sqrt(distmax) + avg_dist/(10.0*_NBC);
// out << constraint << "\n";
ep.set_bb_output ( ic++ , 0.0 );
ep.set_bb_output ( _M , constraint);
return true;
}