Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.13091/6049
Title: | Chaotic Artificial Algae Algorithm for Solving Global Optimization With Real-World Space Trajectory Design Problems | Authors: | Turkoğlu, Bahaeddin Uymaz, Sait Ali Kaya, Ersin |
Keywords: | Artificial algae algorithm Chaotic maps Global optimization Engineering design Space trajectory mission Firefly Algorithm |
Publisher: | Springer Heidelberg | Abstract: | The artificial algae algorithm (AAA) is a recently introduced metaheuristic algorithm inspired by the behavior and characteristics of microalgae. Like other metaheuristic algorithms, AAA faces challenges such as local optima and premature convergence. Various strategies to address these issues and enhance the performance of the algorithm have been proposed in the literature. These include levy flight, local search, variable search, intelligent search, multi-agent systems, and quantum behaviors. This paper introduces chaos theory as a strategy to improve AAA's performance. Chaotic maps are utilized to effectively balance exploration and exploitation, prevent premature convergence, and avoid local minima. Ten popular chaotic maps are employed to enhance AAA's performance, resulting in the chaotic artificial algae algorithm (CAAA). CAAA's performance is evaluated on thirty benchmark test functions, including unimodal, multimodal, and fixed dimension problems. The algorithm is also tested on three classical engineering problems and eight space trajectory design problems at the European Space Agency. A statistical analysis using the Friedman and Wilcoxon tests confirms that CAA demonstrates successful performance in optimization problems. | URI: | https://doi.org/10.1007/s13369-024-09222-z https://hdl.handle.net/20.500.13091/6049 |
ISSN: | 2193-567X 2191-4281 |
Appears in Collections: | Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections |
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