A global optimizer inspired from the survival strategies of flying foxes

• Published in: Engineering with computers Vol. 39; no. 2; pp. 1583 - 1616
• Main Authors: Zervoudakis, Konstantinos, Tsafarakis, Stelios
• Format: Journal Article
• Language: English
• Published: London Springer London 01.04.2023; Springer Nature B.V
• Subjects: Algorithms; CAE) and Design; Calculus of Variations and Optimal Control; Optimization; Classical Mechanics; Computer Science; Computer-Aided Engineering (CAD; Control; Engineering; Exploitation; Fuzzy logic; Genetic algorithms; Global optimization; Heuristic methods; Math. Applications in Chemistry; Mathematical and Computational Engineering; Optimization algorithms; Original Article; Parameters; Survival; Systems Theory; Global optimization; Metaheuristic; Nature-inspired algorithm; Flying Foxes Optimization; Self-tuning algorithm
• ISSN: 0177-0667; 1435-5663
• DOI: 10.1007/s00366-021-01554-w

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. Graphical abstract