Eduardo Segredo and team win the Gold Medal (and first in the "Biathlon" and "High Jump" categories) in the 2016 Genopt Competition

29/05/2016

Congratulations to Eduardo Segredo, whose algorithm has won two prizes at the annual GENOPT competition

While comparing results on benchmark functions is a widely used practice to demonstrate the competitiveness of global optimization algorithms, fixed benchmarks can lead to a negative data mining process. The motivated researcher can “persecute” the algorithm choices and parameters until the final designed algorithm “confesses” positive results for the specific benchmark.  

To avoid the negative data mining effect, the GENOPT contest makes a set of generators available to participants to test off-line and online tuning schemes,  then runs a final competition based on random seeds only communicated in the final phase.

A dashboard will reflect the current ranking of the participants, who are encouraged to exchange preliminary results and opinions.

The High Jump prize is awarded to the submission that typically jumps higher than the others, according to the “Record at Checkpoints” criterion 

The Target Shooting prize is  awarded to the submission whose runs typically achieve higher success rates in the quest for the true global minimum

The Biathlon prize is awarded to the submission achieving the highest cumulative ranking in the two previous categories

The winners will be celebrated at LION 2016 - the Learning and Intelligent OptimizatioN Conference, on Ischia Island (Napoli), Italy, 29 May - 1 June, 2016

The Leaderboard is available at the GenOpt site - Eduardo's algorithm won the Biathlon and High Jump Categories, and overall Gold Medal






 
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Associated people

Emma Hart
Director of CEC
e.hart@napier.ac.uk
+44 131 455 2783
Ben Paechter
Director of Research
b.paechter@napier.ac.uk
+44 131 455 2764
Bio-inspired Computing
The Bio-Inspired Algorithms group within the Centre for Algorithms, Visualisation and Evolving Systems is a large and thriving group with interests in nature-inspired computing that include Evolutionary Computing, Hyper-Heuristics, Artificial Immune Systems and Swarm Intelligence.

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