Results of the GECCO'2016 2-OBJ Track
"Raw" Result Data
On each problem participants were judged by the overall dominated hypervolume within the given budget of function evaluations. There were 7 participants in the field. The best function value per problem and participant (1000 times 7 double precision numbers) is listed in this text file.
Participant Ranking
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 | Simon Wessing | Restarted local search + SMS-EMOA | link | 727.395 | 2516 | ||
2 | DIKU, University of Copenhagen | UB-MO-CMA-ES | unbounded population CMA-ES same as in BBOB2016 2-obj benchmark | 639.549 | 2991 | ||
3 | Poly Montreal | 284.103 | 3851 | ||||
4 | Artelys | Artelys Knitro | Artelys Knitro used in derivative-free mode with multistart | link | link | 252.641 | 4423 |
5 | Grays | 241.454 | 3833 | ||||
6 | Mohammadamin Jahanpour and Bryan Tolson | Pareto archived dynamically dimensioned search (PA-DDS) | Convex Hull Contribution was used as selection metric for PA-DDS | link | link | 168.089 | 4376 |
7 | Al Jimenez | Curved Trajectories Algorithm (CTA) | link | 53.8935 | 6010 |
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.