Green Anaconda Optimization: A New Bio-Inspired Metaheuristic Algorithm for Solving Optimization Problems
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18470%2F23%3A50020368" target="_blank" >RIV/62690094:18470/23:50020368 - isvavai.cz</a>
Result on the web
<a href="https://www.mdpi.com/2313-7673/8/1/121" target="_blank" >https://www.mdpi.com/2313-7673/8/1/121</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/biomimetics8010121" target="_blank" >10.3390/biomimetics8010121</a>
Alternative languages
Result language
angličtina
Original language name
Green Anaconda Optimization: A New Bio-Inspired Metaheuristic Algorithm for Solving Optimization Problems
Original language description
A new metaheuristic algorithm called green anaconda optimization (GAO) which imitates the natural behavior of green anacondas has been designed. The fundamental inspiration for GAO is the mechanism of recognizing the position of the female species by the male species during the mating season and the hunting strategy of green anacondas. GAO’s mathematical modeling is presented based on the simulation of these two strategies of green anacondas in two phases of exploration and exploitation. The effectiveness of the proposed GAO approach in solving optimization problems is evaluated on twenty-nine objective functions from the CEC 2017 test suite and the CEC 2019 test suite. The efficiency of GAO in providing solutions for optimization problems is compared with the performance of twelve well-known metaheuristic algorithms. The simulation results show that the proposed GAO approach has a high capability in exploration, exploitation, and creating a balance between them and performs better compared to competitor algorithms. In addition, the implementation of GAO on twenty-one optimization problems from the CEC 2011 test suite indicates the effective capability of the proposed approach in handling real-world applications.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Biomimetics
ISSN
2313-7673
e-ISSN
2313-7673
Volume of the periodical
8
Issue of the periodical within the volume
1
Country of publishing house
CH - SWITZERLAND
Number of pages
60
Pages from-to
"Article Number:121"
UT code for WoS article
000957397200001
EID of the result in the Scopus database
2-s2.0-85151386210