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Results of the GECCO'2018 1-OBJ 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 17 participants in the field. The best function value per problem and participant (1000 times 17 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 Nbelkhir Feature Based Algorithm Selection Feature Based Algorithm Selection + algorithm scheduling: a set of 20 optimizers including CMA-ES, BFGS, ... 1077.06 3898
2 Danil Shkarupin 878.68 4407
3 radka 817.503 4747
4 avaneev biteopt2017 link 744.583 4730
5 jpsbook 730.328 5093
6 Al Jimenez 578.137 5951
7 Poly Montreal MADS + VNS + NM 509.345 6421
8 Artelys 275.369 9915
9 GERAD PSD-MADS Serial version of PSD-MADS, based on MADS and using the NOMAD software. link link 244.434 7665
10 mini-mlog GAPSO A swarm approach utilizing CPSO, SPSO, DE, Simplex and quasi-Newton methods link link 140.54 8320
11 Jeremy Research algorithm 105.573 8591
12 LocalSolver 38.6977 10664
13 kadiri 10.7097 12314
14 djagodzi 6.53201 13656
15 anonymous 3.63873 14834

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.