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A global optimizer inspired from the survival strategies of flying foxes

Zervoudakis Konstantinos, Tsafarakis Stelios

Απλή Εγγραφή


URIhttp://purl.tuc.gr/dl/dias/631AAC33-D6FE-42AB-9707-C49B1A7318F8-
Αναγνωριστικόhttps://doi.org/10.1007/s00366-021-01554-w-
Αναγνωριστικόhttps://doi.org/10.1007/s00366-021-01554-w-
Γλώσσαen-
Μέγεθος34 pagesen
ΤίτλοςA global optimizer inspired from the survival strategies of flying foxesen
ΔημιουργόςZervoudakis Konstantinosen
ΔημιουργόςΖερβουδακης Κωνσταντινοςel
ΔημιουργόςTsafarakis Steliosen
ΔημιουργόςΤσαφαρακης Στελιοςel
ΕκδότηςSpringer Natureen
ΠεριγραφήThis research is co-financed by Greece and the European Union (European Social Fund- ESF) through the Operational Programme «Human Resources Development, Education and Lifelong Learning» in the context of the project “Strengthening Human Resources Research Potential via Doctorate Research” (MIS-5000432), implemented by the State Scholarships Foundation (ΙΚΥ).el
ΠερίληψηThe 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.en
ΤύποςPeer-Reviewed Journal Publicationen
ΤύποςΔημοσίευση σε Περιοδικό με Κριτέςel
Άδεια Χρήσηςhttp://creativecommons.org/licenses/by/4.0/en
Ημερομηνία2024-02-08-
Ημερομηνία Δημοσίευσης2023-
Θεματική ΚατηγορίαFlying Foxes Optimizationen
Θεματική ΚατηγορίαNature-inspired algorithmen
Θεματική ΚατηγορίαGlobal optimizationen
Θεματική ΚατηγορίαSelf-tuning algorithmen
Θεματική ΚατηγορίαMetaheuristicen
Βιβλιογραφική ΑναφοράK. 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.en

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