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HSFA: A novel firefly algorithm based on a hierarchical strategy
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DOI：10.1016/j.knosys.2023.110950.png)
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The firefly algorithm (FA) is a well-known metaheuristic algorithm that has demonstrated effectiveness and superiority in a variety of optimization tasks. To alleviate the oscillation caused by fireflies during the search process and improve the solution quality of the FA, this paper proposes an improved FA based on the hierarchy strategy (HSFA). In the HSFA, the firefly population was separated into elite and non-elite groups based on fitness values, and distinct attractive models were used for each group to improve the performance of the HSFA from the perspective of exploration and exploitation capabilities. This enhances the convergence speed and solution quality of the algorithm. The HSFA was run on two sets of standard benchmark functions, and its performance was evaluated using two practical engineering design problems. The experimental results demonstrate that the HSFA outperforms state-of-the-art optimization algorithms.(c) 2023 Elsevier B.V. All rights reserved.
Keyword:
Firefly algorithm
Metaheuristic algorithm
Hierarchical strategy
Swarm intelligence
期刊
K
IF:
7.6
论文数:
1.2W
被引数:
4.5W
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分享收藏Randomly attracted firefly algorithm with neighborhood search and dynamic parameter adjustment mechanism.png)
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