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There is no single best algorithm that works for every situation. The Artificial Bee Colony (ABC) algorithm is popular but it suffers from limitations like slow convergence and getting stuck in local optima in some problems. This study introduces a hybrid algorithm called the Bee Eel Forage Algorithm (BEFA), inspired by the collective foraging behavior of honeybees and the group foraging behavior exhibited by electric eels. BEFA incorporates employed bee, resting, and scout bee phases to achieve efficient exploration and exploitation with the potential to overcome limitations of algorithms like ABC. To evaluate its effectiveness, BEFA is applied to the welded beam design problem, aiming to minimize cost. The results demonstrate that BEFA outperforms competitors (ABC, PSO, WOA) by achieving the lowest mean and standard deviation across 30 independent runs and identifying the best minimum function value. BEFA's superior performance suggests its potential as a valuable tool for the welded beam design problem.

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A Hybridized Artificial Bee Colony and Electric Eel Foraging Algorithm for Constrained Engineering Problem

  • 会议论文

  • 发表日期：

    2025年

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  • Wei Wen Lee,
  • Mohd Ruzaini bin Hashim,
  • Chin Kim Gan

摘要

There is no single best algorithm that works for every situation. The Artificial Bee Colony (ABC) algorithm is popular but it suffers from limitations like slow convergence and getting stuck in local optima in some problems. This study introduces a hybrid algorithm called the Bee Eel Forage Algorithm (BEFA), inspired by the collective foraging behavior of honeybees and the group foraging behavior exhibited by electric eels. BEFA incorporates employed bee, resting, and scout bee phases to achieve efficient exploration and exploitation with the potential to overcome limitations of algorithms like ABC. To evaluate its effectiveness, BEFA is applied to the welded beam design problem, aiming to minimize cost. The results demonstrate that BEFA outperforms competitors (ABC, PSO, WOA) by achieving the lowest mean and standard deviation across 30 independent runs and identifying the best minimum function value. BEFA's superior performance suggests its potential as a valuable tool for the welded beam design problem.