Parallel DDS for Approximation of Uncertainty (PDDSAU)
Iter  Run   obj.function  K1            K2            Kback         
0     16    4.179107E+02  4.056975E-10  1.901332E-03  1.137228E+00  
1     5     2.848040E+03  8.850449E-08  1.751487E-09  7.505668E-01  
2     21    8.106038E+02  3.237734E-06  3.307327E-08  8.585963E-01  
3     20    8.102138E+02  1.210121E-10  1.291213E+00  8.491283E-01  
4     14    1.420992E+02  1.056468E+00  1.589426E-02  9.482827E-01  
5     8     5.709146E+03  2.078451E-04  7.831063E-06  1.679760E+00  
6     11    3.744522E+03  1.029827E-02  1.072015E-04  1.507235E+00  
7     16    4.202358E+02  1.421554E-08  8.810293E+02  8.830182E-01  
8     1     6.501176E+01  7.644051E+02  3.455068E-01  1.055246E+00  
9     7     3.101814E+03  2.977288E-06  1.039614E-02  7.413899E-01  
10    14    1.570370E+02  2.400109E-03  1.565021E-02  9.436010E-01  
11    9     1.214757E+03  2.841720E-04  9.681777E-10  1.252036E+00  
12    14    7.359044E+02  1.508534E-10  5.916320E-04  1.188810E+00  
13    20    4.391721E+02  1.060727E-02  2.564478E-07  1.141222E+00  
14    9     1.386130E+03  5.847193E-09  5.245963E-02  8.169224E-01  
15    15    1.201849E+02  6.502220E+00  1.137764E+01  9.358716E-01  
16    10    1.977386E+01  5.649888E+01  3.269218E+02  9.722939E-01  
17    1     5.078264E+02  3.499249E-07  7.927865E-05  8.882729E-01  
18    5     4.489456E+01  5.029954E-05  3.778265E+02  1.026509E+00  
19    6     6.764879E+02  4.418719E-08  3.611579E-01  1.177127E+00  
20    11    1.121724E+01  1.565195E-01  3.050653E+01  9.882121E-01  
21    6     5.634223E+02  3.033332E-05  1.576280E-09  8.821105E-01  
22    3     8.822623E+03  1.212859E-02  7.722188E-02  6.134896E-01  
23    16    2.281587E+03  2.023254E-10  2.198126E-04  1.368542E+00  
24    10    7.555730E+02  2.100466E-04  6.612453E+01  8.489079E-01  

Algorithm Metrics
Algorithm                : DDS for Approximating Uncertainty (DDSAU)
Perturbation Value       : 0.20
Desired # of Samples     : 25
Actual # of Samples      : 25
Min DDS Evals per Sample : 50
Max DDS Evals per Sample : 100
Behavioral Threshold     : 1.000000E+04
Randomize samples?       : yes
Revise Previous DDS AU?  : no

List of Behavioral Solutions
Iter  Run   obj.function            K1            K2         Kback  
0     16    4.179107E+02  4.056975E-10  1.901332E-03  1.137228E+00  
1     5     2.848040E+03  8.850449E-08  1.751487E-09  7.505668E-01  
2     21    8.106038E+02  3.237734E-06  3.307327E-08  8.585963E-01  
3     20    8.102138E+02  1.210121E-10  1.291213E+00  8.491283E-01  
4     14    1.420992E+02  1.056468E+00  1.589426E-02  9.482827E-01  
5     8     5.709146E+03  2.078451E-04  7.831063E-06  1.679760E+00  
6     11    3.744522E+03  1.029827E-02  1.072015E-04  1.507235E+00  
7     16    4.202358E+02  1.421554E-08  8.810293E+02  8.830182E-01  
8     1     6.501176E+01  7.644051E+02  3.455068E-01  1.055246E+00  
9     7     3.101814E+03  2.977288E-06  1.039614E-02  7.413899E-01  
10    14    1.570370E+02  2.400109E-03  1.565021E-02  9.436010E-01  
11    9     1.214757E+03  2.841720E-04  9.681777E-10  1.252036E+00  
12    14    7.359044E+02  1.508534E-10  5.916320E-04  1.188810E+00  
13    20    4.391721E+02  1.060727E-02  2.564478E-07  1.141222E+00  
14    9     1.386130E+03  5.847193E-09  5.245963E-02  8.169224E-01  
15    15    1.201849E+02  6.502220E+00  1.137764E+01  9.358716E-01  
16    10    1.977386E+01  5.649888E+01  3.269218E+02  9.722939E-01  
17    1     5.078264E+02  3.499249E-07  7.927865E-05  8.882729E-01  
18    5     4.489456E+01  5.029954E-05  3.778265E+02  1.026509E+00  
19    6     6.764879E+02  4.418719E-08  3.611579E-01  1.177127E+00  
20    11    1.121724E+01  1.565195E-01  3.050653E+01  9.882121E-01  
21    6     5.634223E+02  3.033332E-05  1.576280E-09  8.821105E-01  
22    3     8.822623E+03  1.212859E-02  7.722188E-02  6.134896E-01  
23    16    2.281587E+03  2.023254E-10  2.198126E-04  1.368542E+00  
24    10    7.555730E+02  2.100466E-04  6.612453E+01  8.489079E-01  
