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2025 | OriginalPaper | Buchkapitel

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

verfasst von : Michael S. Packianather, Azar Imanguliyev, D. T. Pham

Erschienen in: Intelligent Engineering Optimisation with the Bees Algorithm

Verlag: Springer Nature Switzerland

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Abstract

This chapter discusses modifications to the basic Bees Algorithm to enhance its performance. The proposed changes involve adding an early 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 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 Algorithm performed better than the basic version. The results were also compared with those of other swarm-based optimisation methods.

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Titel: Enhanced Bees Algorithm Implementing Early Neighbourhood Search with Efficiency-Based Recruitment
verfasst von: Michael S. Packianather
Azar Imanguliyev
D. T. Pham
Verlag: Springer Nature Switzerland
Buch: Intelligent Engineering Optimisation with the Bees Algorithm
Print ISBN: 978-3-031-64935-6

Electronic ISBN: 978-3-031-64936-3

Copyright-Jahr: 2025
DOI: https://doi.org/10.1007/978-3-031-64936-3_1

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