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A global optimizer inspired from the survival strategies of flying foxes

Zervoudakis Konstantinos, Tsafarakis Stelios

Πλήρης Εγγραφή


URI: http://purl.tuc.gr/dl/dias/631AAC33-D6FE-42AB-9707-C49B1A7318F8
Έτος 2023
Τύπος Δημοσίευση σε Περιοδικό με Κριτές
Άδεια Χρήσης
Λεπτομέρειες
Βιβλιογραφική Αναφορά 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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Περίληψη

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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