On selection of a benchmark by determining the algorithms' qualities

The authors got the motivation for writing the article based on an issue, with which developers of the newly developed nature-inspired algorithms are usually confronted today: How to select the test benchmark such that it highlights the quality of the developed algorithm most fairly? In line with th...

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Detalhes bibliográficos
Autores: Fister, Iztok, Brest, Janez, Iglesias Prieto, Andrés|||0000-0002-5672-8274, Gálvez Tomida, Akemi|||0000-0002-2100-2289, Deb, Suash, Fister, Iztok Jr
Tipo de documento: artigo
Data de publicação:2021
País:España
Recursos:Universidad de Cantabria (UC)
Repositório:UCrea Repositorio Abierto de la Universidad de Cantabria
Idioma:inglês
OAI Identifier:oai:repositorio.unican.es:10902/23734
Acesso em linha:http://hdl.handle.net/10902/23734
Access Level:Acceso aberto
Palavra-chave:Evolutionary algorithms
Benchmark functions
Differential evolution
Descrição
Resumo:The authors got the motivation for writing the article based on an issue, with which developers of the newly developed nature-inspired algorithms are usually confronted today: How to select the test benchmark such that it highlights the quality of the developed algorithm most fairly? In line with this, the CEC Competitions on Real-Parameter Single-Objective Optimization benchmarks that were issued several times in the last decade, serve as a testbed for evaluating the collection of nature-inspired algorithms selected in our study. Indeed, this article addresses two research questions: (1) How the selected benchmark affects the ranking of the particular algorithm, and (2) If it is possible to find the best algorithm capable of outperforming all the others on all the selected benchmarks. Ten outstanding algorithms (also winners of particular competitions) from different periods in the last decade were collected and applied to benchmarks issued during the same time period. A comparative analysis showed that there is a strong correlation between the rankings of the algorithms and the benchmarks used, although some deviations arose in ranking the best algorithms. The possible reasons for these deviations were exposed and commented on.