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. To avoid this negative effect, the GENOPT contest benchmarks can be used which are based on randomized function generators, designed for scientific experiments, with fixed statistical characteristics but individual variation of the generated instances. The generators are available to participants for off-line tests and online tuning schemes, but the final competition is based on random seeds communicated in the last phase through a cooperative process. A brief presentation and discussion of the methods and results obtained in the framework of the GENOPT contest are given in this contribution.

GENOPT 2016: Design of a GENeralization-based challenge in global OPTimization / Battiti, Roberto; Sergeyev, Yaroslav; Brunato, Mauro; Kvasov, Dmitri. - 1776:(2016), pp. 060005.1-060005.4. (Intervento presentato al convegno NUMTA 2016 tenutosi a Pizzo Calabro, Italia nel 19th-25th June 2016) [10.1063/1.4965339].

GENOPT 2016: Design of a GENeralization-based challenge in global OPTimization

Battiti, Roberto;Brunato, Mauro;
2016-01-01

Abstract

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. To avoid this negative effect, the GENOPT contest benchmarks can be used which are based on randomized function generators, designed for scientific experiments, with fixed statistical characteristics but individual variation of the generated instances. The generators are available to participants for off-line tests and online tuning schemes, but the final competition is based on random seeds communicated in the last phase through a cooperative process. A brief presentation and discussion of the methods and results obtained in the framework of the GENOPT contest are given in this contribution.
2016
Numerical Computations (NUMTA–2016): Proceedings of the 2nd International Conference “Numerical Computations: Theory and Algorithms”
Melville, NY
American Institute of Physics Inc.
9780735414389
Battiti, Roberto; Sergeyev, Yaroslav; Brunato, Mauro; Kvasov, Dmitri
GENOPT 2016: Design of a GENeralization-based challenge in global OPTimization / Battiti, Roberto; Sergeyev, Yaroslav; Brunato, Mauro; Kvasov, Dmitri. - 1776:(2016), pp. 060005.1-060005.4. (Intervento presentato al convegno NUMTA 2016 tenutosi a Pizzo Calabro, Italia nel 19th-25th June 2016) [10.1063/1.4965339].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/182358
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