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A global optimizer inspired from the survival strategies of flying foxes

Zervoudakis Konstantinos, Tsafarakis Stelios

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URI: http://purl.tuc.gr/dl/dias/631AAC33-D6FE-42AB-9707-C49B1A7318F8
Year 2023
Type of Item Peer-Reviewed Journal Publication
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Bibliographic Citation K. Zervoudakis and S. Tsafarakis, “A global optimizer inspired from the survival strategies of flying foxes,” Eng. Comput., vol. 39, no. 2, pp. 1583–1616, Apr. 2023, doi: 10.1007/s00366-021-01554-w. https://doi.org/10.1007/s00366-021-01554-w
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Summary

The aim of the current paper is to introduce a global optimization algorithm, inspired from the survival strategies of flying foxes during a heatwave, called as Flying Foxes Optimization (FFO). The proposed method exploits a Fuzzy Logic (FL) technique to determine the parameters individually for each solution, thus resulting in a parameters-free optimization algorithm. To evaluate FFO, 56 benchmark functions, including the CEC2017 test function suite and three real-world engineering problems, are employed and its performance is compared to those of state-of-the-art metaheuristics, when it comes to global optimization. The comparison results reveal that the proposed FFO optimizer constitutes a powerful attractive alternative for global optimization.

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