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The Simplified Aquila Optimization Algorithm
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OA
AI
DOI：10.1109/ACCESS.2022.3153727.png)
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摘要
En 中文
Considering the complicated multimodality, separability, scalability, symmetry characteristics of real-world engineering problems, we are still under the way to find more capable algorithms to solve them. The Aquila optimization (AO) algorithm was just proposed recently, however, the original version of this algorithm had some defects in the exploitation procedure, and resulted in incapability to exploit more information. Therefore, a simplified improved AO (IAO) algorithm was proposed and the equation controlling the exploitation procedure was removed, the former two strategies were kept and the latter two were dropped. To confirm the capability of the proposed IAO, simulation experiments on unimodal, multimodal benchmark functions and the CEC21 basic functions were carried out. Simulation experiments on three famous real-world engineering problems were also carried out. Comparison were made with the original AO algorithm, and some other newly proposed nature-inspired algorithms. Results on benchmark functions and the CEC14 basic functions verified the better performance, however, results on the real-world engineering problems demonstrated an incapable conclusion. Detailed future work is needed to tell the reason.
Keyword:
Optimization
Mathematical models
Benchmark testing
Statistics
Sociology
Convergence
Licenses
Aquila optimization algorithm
meta-heuristic algorithm
nature-inspired algorithm
benchmark function
engineering problems
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
机构
引用论文
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Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm蛾焰优化算法: 一种新的自然启发启发式范式
PREAI
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