Repulsion-Propulsion Firefly Algorithm with Fast Convergence to Solve Highly Multi-Modal Problems

Abhijit Banerjee, D. Ghosh, Suvrojit Das
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引用次数: 1

Abstract

This paper proposes a modified firefly algorithm (PropFA) to solve highly multimodal problems with fast convergence. In this algorithm every firefly is fitted with a short term memory which facilitates the "Repulsion" force acting on every firefly whereas the introduction of brightness of the best firefly in the movement equation facilitates "Propulsion" force acting on the firefly. Furthermore; no firefly is allowed to move beyond its maximum stride parameter to prevent premature convergence. All other parameters α,β and γ and are designed to be adaptive to suite to almost all multimodal problems without setting them to any a-priori values. Efficiency of PropFA is then verified over six standard test functions. In all of them it is observed that PropFA converges faster than FA and PSO.
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求解高度多模态问题的快速收敛的斥力-推进萤火虫算法
本文提出了一种改进的萤火虫算法(PropFA),用于求解高度多模态问题,收敛速度快。在该算法中,每只萤火虫都具有短期记忆,这有利于作用于每只萤火虫的“斥力”,而在运动方程中引入最佳萤火虫的亮度,则有利于作用于萤火虫的“推进力”。此外;不允许任何萤火虫移动超过其最大步幅参数,以防止过早收敛。所有其他参数α,β和γ和被设计为自适应套件几乎所有的多模态问题,而无需设置任何先验值。然后通过六个标准测试功能验证PropFA的效率。在所有这些算法中,profa的收敛速度都快于FA和PSO。
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