Nature-Inspired Algorithms in Real-World Optimization Problems
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Date
2017-06-01
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ORCID
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Referee
Mark
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Publisher
Institute of Automation and Computer Science, Brno University of Technology
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Abstract
Eight popular nature inspired algorithms are compared with the blind random search and three advanced adaptive variants of differential evolution (DE) on real-world problems benchmark collected for CEC 2011 algorithms competition. The results show the good performance of the adaptive DE variants and their superiority over the other algorithms in the test problems. Some of the nature-inspired algorithms perform even worse that the blind random search in some problems. This is a strong argument for recommendation for application, where well-verified algorithm successful in competitions should be preferred instead of developing some new algorithms.
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Citation
Mendel. 2017 vol. 23, č. 1, s. 7-14. ISSN 1803-3814
https://mendel-journal.org/index.php/mendel/article/view/42
https://mendel-journal.org/index.php/mendel/article/view/42
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Peer-reviewed
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en