# Post-processing parameters

If post processing is activated, it is performed after every optimization run and it may be triggered using the solutions of the last optimization run by the "Post process" button. Post processing performs an initial clustering of the solutions with the given sigma interval (density-based clustering), and on the set of best representative solutions from all clusters it performs a hill-climbing run for refinement. After the HC step the set is clustered again to filter out solutions which converged during the HC.

The results of the post processing are displayed in the text window (and/or stats output file) and show a coarse distribution of the final solutions as well as the explicit vectors of the n best solutions obtained, where n is set as printNBest parameter. If post-processing is started several times in a row, the initial solution set is the same, namely the one found by optimization. Thereby one can guess, e.g., how close the solutions are to each other and how closely they have converged during optimization itself.