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This chapter discusses modifications to the basic Bees AlgorithmBasic Bees Algorithm to enhance its performance. The proposed changes involve adding an early neighbourhood scanningEarly neighbourhood scanning step to determine promising areas from which to start the local search operation and making the recruitment process dynamic by varying the number of bees recruited to exploit a patch according to how efficiently it has been exploited. The enhanced version of the Bees AlgorithmBees algorithm was applied to well-known complex continuous benchmark functions with high dimensions to find their optima. The results obtained from this study show that the new Bees AlgorithmBees algorithm performed better than the basic version. The results were also compared with those of other swarm-based optimisationOptimisation methods.

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Enhanced Bees Algorithm Implementing Early Neighbourhood Search with Efficiency-Based Recruitment

  • 章节

  • 发表日期：

    2025年

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  • Michael S. Packianather,
  • Azar Imanguliyev,
  • D. T. Pham

摘要

This chapter discusses modifications to the basic Bees AlgorithmBasic Bees Algorithm to enhance its performance. The proposed changes involve adding an early neighbourhood scanningEarly neighbourhood scanning step to determine promising areas from which to start the local search operation and making the recruitment process dynamic by varying the number of bees recruited to exploit a patch according to how efficiently it has been exploited. The enhanced version of the Bees AlgorithmBees algorithm was applied to well-known complex continuous benchmark functions with high dimensions to find their optima. The results obtained from this study show that the new Bees AlgorithmBees algorithm performed better than the basic version. The results were also compared with those of other swarm-based optimisationOptimisation methods.