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.

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	Artelys	Artelys Knitro	Artelys Knitro used in derivative-free mode with multistart	link	link	1060.12	4331
2	Mickey					907.073	4968
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.	link		724.869	5722
4	MOVING	XolEAO Toolbox (alpha version)				610.11	6067
5	Al Jimenez	Curved Trajectories Algorithm (CTA)		email	link	554.538	6345
6	Lepagnot	HILS	Hybrid algorithm			438.551	7248
7	anonymous					338.822	7725
8	Giacomo Nannicini					313.901	7986
9	bujok					276.144	8720
10	Poly Montreal					246.477	9151
11	radka					181.888	9454
12	djagodzi					156.257	9045
13	Brevilliers	BSA-DE-SA				143.87	9286
14	jarabas					47.6015	11528
15	Sumaiya Iqbal					32.7853	12420

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.