jcobyla successful termination when constraints violated

import com.cureos.numerics.Calcfc;
import com.cureos.numerics.Cobyla;

public class JCobylaTest {

  public static void main(String[] args) {

    double[] optimize = new double[8];
    for (int i = 0; i < optimize.length; i++) {
      optimize[i] = 1d/optimize.length;
    }

    Cobyla.FindMinimum(new Calcfc() {

      @Override
      public double Compute(int n, int m, double[] x, double[] con) {

        // ----- vars have to be non negative -----
        for (int i = 0; i < x.length; i++) {
          con[i] = x[i];
        }
        // ----- END -----
        // ----- sum of vars have to be approximately 1 -----
        double sum = 0;
        for (int i = 0; i < x.length; i++) {
          sum += x[i];
        }
        con[x.length] = sum - 0.9999;
        con[x.length + 1] = 1.0001 - sum;
        // ----- END -----
        // ----- pnorm_1(matrix * x) <= 0.06651 -----
        double[][] matrix = {{-0.25, -0.25, 0.75, 0.75, -0.25, -0.25, 0.75, 0.75},
                             {0.0, -0.8, 0.0, 0.2, 0.0, -0.8, 0.0, 0.2},
                             {0.0, 0.0, 0.0, 0.0, -0.6, -0.6, 0.4, 0.4},
                             {0.0, 0.0, -0.7, -0.7, 0.0, 0.0, 0.3, 0.3},
                             {0.0, 0.0, -0.5, 0.5, 0.0, 0.0, -0.5, 0.5},
                             {-0.05, -0.05, 0.0, 0.0, 0.95, 0.95, 0.0, 0.0},
                             {-0.01, 0.99, 0.0, 0.0, -0.01, 0.99, 0.0, 0.0}};
        double[] matrix_m_x = new double[matrix.length];
        sum = 0;
        for (int i = 0; i < matrix.length; i++) {
          for (int j = 0; j < matrix[i].length; j++) {
            matrix_m_x[i] = matrix_m_x[i] + matrix[i][j] * x[j];
          }
          sum += Math.abs(matrix_m_x[i]);
        }
        con[x.length + 2] = 0.06651 - sum;
        // ----- END -----
        // ----- maximise entropy -----
        double entropie = 0;
        for (int i = 0; i < x.length; i++) {
          double d = x[i];
          if (Double.compare(d, 0) <= 0) {
            continue;
          }
          entropie -= d *log2(d);
        }
        // ----- END -----

        return -entropie;
      }

    }, 8, 11, optimize, /*1*/0.001, 1.0e-6, 3, 1000);
  }

  private static double log2(double val) {
    return Math.log10(val) / Math.log(2);
  }
}