Title: Winner of the generalization-based contest in global optimization (GENOPT 2017)
Short description: The Generalization-based Contest in Global Optimization (GENOPT, ) is a special session of the Learning and Intelligent Optimization Conference (LION). During LION 11 (June 19–21, 2017, Nizhny Novgorod, Russia, ), the GABRLS algorithm won the 1st prize in all partial categories (the speed of convergence, the number of tasks solved and the overall ranking) on a test suite of 1800 multidimensional problems. The GENOPT contest benchmarks are based on randomized function generators, designed for scientific experiments, with fixed statistical characteristics but an individual variation of the generated instances. The generators are available to participants for on-line tests and online tuning schemes, but the final competition is based on random seeds communicated in the last phase through a cooperative process. In this global optimization challenge, it was used a technique to improve the behavior of an optimization algorithm on a wide spectrum of problems.
 Battiti, R., Sergeyev, Y.D., Brunato, M., Kvasov, D.E.: GENOPT 2016: design of a generalization-based challenge in global optimization. In: Sergeyev, Y.D., Kvasov, D.E., Dell’Accio, F., Mukhametzhanov, M.S. (eds.) AIP Conference Proceedings, vol. 1776, no. 060005. AIP Publishing (2016)
 Battiti R., Kvasov D., Sergeyev Y. (eds) Learning and Intelligent Optimization. LION 2017. Lecture Notes in Computer Science, vol 10556. Springer, Cham. https://doi.org/10.1007/978-3-319-69404-7_20