Results of the GECCO'2016 1-OBJ expensive Track
"Raw" Result Data
On each problem participants were judged by the best (lowest) function value achieved within the given budget of function evaluations. There were 15 participants in the field. The best function value per problem and participant (1000 times 15 double precision numbers) is listed in this text file.
Participants were ranked based on aggregated problem-wise ranks (details here and here). The following results table lists participants with overall scores (higher is better) and the sum of ranks over all problems (lower is better) The table can be sorted w.r.t. these criteria.
|rank||participant||method name||method description||software||paper||score||sum of ranks|
|1||Artelys||Artelys Knitro||Artelys Knitro used in derivative-free mode with multistart||link||link||1060.12||4331|
|3||Simon Wessing||Restarted local search||
The same code as for BBComp2016-1OBJ, but with a slightly different configuration. Local search algorithms are the same, but only restarted local search is used. The second difference is that all ever sampled points are put into an archive and considered in the global stage.
|4||MOVING||XolEAO Toolbox (alpha version)||610.11||6067|
|5||Al Jimenez||Curved Trajectories Algorithm (CTA)||link||554.538||6345|
Visualization of Performance Data
The following figure shows an aggregated view on the performance data.
The following figures show the same data, but separately for each problem dimension.