I am doing a multi-objective optimization task using Pymoo.org, but I have a hard time understanding the last three columns of the output.
I assume n_nds is the number of nondominant solutions in each generation. However, I don't understand the eps and indicator. Particularly the indicator column. I have come across this page "Display" which is referring readers to A Running Performance Metric and Termination Criterion for Evaluating Evolutionary Multi- and Many-objective Optimization Algorithms.
I have studied half of the paper. However, I have not found any explanations in that regard.
I would appreciate your valuable comments.
n_gen | n_eval | cv (min) | cv (avg) | n_nds | eps | indicator
1 | 42 | 0.00000E+00 | 0.00000E+00 | 14 | - | -
2 | 84 | 0.00000E+00 | 0.00000E+00 | 19 | 0.024237527 | ideal
3 | 126 | 0.00000E+00 | 0.00000E+00 | 6 | 0.091298096 | ideal
4 | 168 | 0.00000E+00 | 0.00000E+00 | 8 | 0.023750728 | f
5 | 210 | 0.00000E+00 | 0.00000E+00 | 7 | 0.002902893 | f
6 | 252 | 0.00000E+00 | 0.00000E+00 | 10 | 0.032567624 | f
7 | 294 | 0.00000E+00 | 0.00000E+00 | 11 | 0.000912191 | f
8 | 336 | 0.00000E+00 | 0.00000E+00 | 12 | 0.076898816 | f
9 | 378 | 0.00000E+00 | 0.00000E+00 | 12 | 0.00000E+00 | f
10 | 420 | 0.00000E+00 | 0.00000E+00 | 14 | 0.065060499 | ideal