Two Novel Instance Selection Methods Combining Algorithm Performance and Landscape Analysis: A Comparative Study in Continuous Optimization

A reliable benchmark library is essential for advancing research in global optimization by enabling fair comparisons and rigorous testing of optimization algorithms across diverse problem landscapes. In this article, we focus on instance selection methods, which aim to choose representative problems...

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Vydané v:	IEEE transactions on cybernetics Ročník PP; s. 1 - 14
Hlavní autori:	Stripinis, Linas, Kudela, Jakub, Paulavicius, Remigijus
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States IEEE 03.11.2025
Predmet:	Algorithm performance Benchmark testing black-box global optimization Cybernetics Euclidean distance exploratory landscape analysis instance selection methods Libraries numerical benchmarking Optimization Reliability Reviews Runtime Training Vectors
ISSN:	2168-2267, 2168-2275, 2168-2275
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