Fennec Fox Optimization: A New Nature-Inspired Optimization Algorithm
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18470%2F22%3A50019363" target="_blank" >RIV/62690094:18470/22:50019363 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/9853509/" target="_blank" >https://ieeexplore.ieee.org/document/9853509/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ACCESS.2022.3197745" target="_blank" >10.1109/ACCESS.2022.3197745</a>
Alternative languages
Result language
angličtina
Original language name
Fennec Fox Optimization: A New Nature-Inspired Optimization Algorithm
Original language description
This paper proposes a new nature-based metaheuristic algorithm called Fennec Fox Optimization (FFA), mimicking two natural behaviors of the animal Fennec Fox in nature. Concretely, Fennec’s digging ability and escape strategy from wild predators were the fundamental inspiration for the proposed FFA. The mathematical model of FFA is presented in two phases based on imitating these two behaviors. First, the efficiency of FFA was evaluated in the optimization of sixty-eight standard benchmark functions and four engineering design problems. Second, FFA performance is challenged against eight well-known optimization algorithms. The optimization results show that FFA perfectly balances exploration and exploitation in searching for the global optimum. Hence, FFA can provide suitable solutions to optimization problems. The comparison of results indicates the superiority of FFA in most objective functions over competitor algorithms in providing the optimal solution.
Czech name
—
Czech description
—
Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10102 - Applied mathematics
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
IEEE Access
ISSN
2169-3536
e-ISSN
2169-3536
Volume of the periodical
10
Issue of the periodical within the volume
srpen
Country of publishing house
US - UNITED STATES
Number of pages
27
Pages from-to
84417-84443
UT code for WoS article
000843554500001
EID of the result in the Scopus database
2-s2.0-85136144062