Can i optimize functions like this?

//Hi, Here is a code trying to find x such that x’Vx*0.5-c’x is minimized constrained on sum of elements of x =1 ,but //it doesn’t work well and I think the problem is on optim.solve which may not be able to optimize the functions like crosssum and dot by //myself, can anyone help to find the mistakes? //Also, any better way to deal with a quadratic programming problem? //Here is the code.

import com.numericalmethod.suanshu.optimization.constrained.general.penaltymethod.PenaltyMethod;
import com.numericalmethod.suanshu.optimization.unconstrained.quasinewton.BFGS;
import com.numericalmethod.suanshu.analysis.function.rn2r1.RealScalarFunction;
import com.numericalmethod.suanshu.number.DoubleUtils;
import com.numericalmethod.suanshu.optimization.constrained.general.ConstrainedProblem;
import com.numericalmethod.suanshu.vector.doubles.Vector;
import com.numericalmethod.suanshu.optimization.constrained.general.constraint.EqualityConstraints;
import com.numericalmethod.suanshu.optimization.constrained.general.constraint.LessThanConstraints;
import com.numericalmethod.suanshu.matrix.doubles.matrixtype.dense.DenseMatrix;
import com.numericalmethod.suanshu.vector.doubles.dense.DenseVector;
import com.numericalmethod.suanshu.matrix.doubles.matrixtype.dense.DenseMatrixUtils;
import java.util.Arrays;
public class Quadprog{
    public static void main(String[]arg){
double [] u = new double []{0.15,0.2,0.4,0.2,0.05,0.3,0.4,0.3,0.06};
DenseMatrix I1 = new DenseMatrix(u,3,3);
double [] a = new double []{1,0.5,0.7};
DenseVector mu = new DenseVector(a);

System.out.println(Arrays.toString(Solver(I1,mu)));
    }

    public static double [] Solver (final DenseMatrix V , final DenseVector mu){

  final double [][] v = DenseMatrixUtils.to2DArray(V);
  final double []y = mu.toArray();
  final int len = mu.length;

    RealScalarFunction f = new RealScalarFunction() {
        public double evaluate (double…x) {
            return 0.5*crosssum(x,v)-dot(x,y);
        }
        public int dimension4Domain() {
                return len;
            }

            public int dimension4Range() {
                return 1;
            }
};

    RealScalarFunction c1 = new RealScalarFunction() {

        public double evaluate (double …x) {
            return sum(x)-1;
        }
          public int dimension4Domain() {
                return len;
            }

        public int dimension4Range() {
            return 1;
        }
};

    RealScalarFunction c2 = new RealScalarFunction() {

    public double evaluate (double …x) {
        return -sum(x);
    }
      public int dimension4Domain() {
            return len;
        }

            public int dimension4Range() {
                return 1;
            }
    };
    ConstrainedProblem problem = new ConstrainedProblem(f,new EqualityConstraints(c1),new LessThanConstraints(c2));
PenaltyMethod optim = new PenaltyMethod(PenaltyMethod.DEFAULT_PENALTY_FUNCTION_FACTORY,
                1e30,
                new BFGS());
        optim.solve(problem, 1e-2, 200);
Vector xmin = optim.search(new DenseVector(new double []{0,0,0}));  // as len=3

        double fxmin = f.evaluate(xmin.toArray());

System.out.println(String.format(“f(%s) = %f”, DoubleUtils.doubleArray2StringArray(xmin.toArray()), fxmin));

return xmin.toArray();

}

    public static double sum (double []x) {   //finding sum of elements of an array
        double sum =0;
         for (int i = 0; i< =x.length-1 ;i++) {
             sum=sum+x;
    }
         return sum;
}

        public static double crosssum (double []x ,double [][]v) {   //finding x’vx
        double sum =0;
         for (int i = 0; i< =x.length-1 ;i++) {
             for (int j=0; j< =x.length-1 ; j++){
          sum=sum+v[j]*x*x[j];
    }

}
    return sum;

}

        public static double dot(double []x , double []y){   //finding dot product of two arrays
            double dot = 0;
            for (int i=0; i< =x.length-1; i++){
                dot = dot +x*y;
            }
            return dot;
        }

}