A Deep Learning-Driven Black-Box Benchmark Generation Method via Exploratory Landscape Analysis

In the context of algorithm selection, the careful design of benchmark functions and problem instances plays a pivotal role in evaluating the performance of optimization methods. Traditional benchmark functions have been criticized for their limited resemblance to real-world problems and insufficien...

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Veröffentlicht in:	Applied sciences Jg. 15; H. 15; S. 8454
Hauptverfasser:	Liang, Haoming, Zhao, Fuqing, Xu, Tianpeng, Zhang, Jianlin
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 01.08.2025
Schlagworte:	algorithm selection problem Algorithms Analysis benchmarking functions Benchmarks black-box optimization Deep learning exploratory landscape analysis Machine learning Methods Neural networks Optimization algorithms Germany
ISSN:	2076-3417, 2076-3417
Online-Zugang:	Volltext
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