I recently ran into an interesting case when performing runtime dynamics and control map diagnostics on my 2 objective formulation of the lake problem with 2 constraints. Although Borg yielded a much better reference set for the control map with a small LHS sample for each algorithm, the other algorithms did better on runtime when limited to 25,000 NFE. In part this resulted from sbx being a dominant operator, allowing those algorithms with it to charge forward while Borg’s adaptive operators took longer to choose it, but it still made me wonder what the default parameters were.
Borg’s were easily found in Table 3 of the paper
Hadka, David, Patrick M. Reed, and Timothy W. Simpson. “Diagnostic assessment of the borg MOEA for many-objective product family design problems.” Evolutionary Computation (CEC), 2012 IEEE Congress on. IEEE, 2012.
found here http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6256466&tag=1.
You can find the default parameters for the MOEAFramework algorithms by inspecting the source code.
Below is a table showing the default parameters that one would specify when control mapping for MOEAFramework Native algorithms followed by where to look in the source code for those, Jmetal, and PISA algorithms and operator default parameters should you want more information. Please note, this table does not provide the actual value of the parameter in all cases as the framework seems to adjust some of the values by certain properties of the problem to attain a final value. These are merely user input values.
To find the default parameters for the algorithms native to the framework (eNSGAII, NSGAII, eMOEA, MOEA/D, and GDE3) you can check the following java class in the source code:
For JMetal Algorithms see:
and for Pisa Algorithms see:
Finally, if you want the default parameters for the operators, you can look in this class:
Thanks to Dave for pointing out where to look in the source code!