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2025 | OriginalPaper | Buchkapitel

Local Optimal Issue in Bees Algorithm: Markov Chain Analysis and Integration with Dynamic Particle Swarm Optimisation Algorithm

verfasst von : JianBang Liu, Mei Choo Ang, Kok Weng Ng, Jun Kit Chaw

Erschienen in: Intelligent Engineering Optimisation with the Bees Algorithm

Verlag: Springer Nature Switzerland

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Abstract

Inspired by the foraging behaviour of bees in nature, the bees algorithm (BA) is a biomimetic optimisation method designed according to how bees work together in choosing food sources and collecting high-quality honey. However, there are only a few mathematical studies on the convergence and optimisation problem of BA in the literature, and most of the BA implementations are dependent on trial-and-error. Thus, this study attempts to use Markov chain theory to enhance the understanding and analysis of BA convergence from the perspectives of the neighbourhood contraction strategy and site abandonment strategy. To improve the optimisation performance of the BA, this study established a combination model of the BA and a dynamic particle swarm optimisation algorithm on the local search process of the BA and the effect of the task allocation of scout bees for target location. Finally, the simulation experiment was conducted in MATLAB using the combination model. The simulation result shows that the probability of the combination model falling into the local optimum is much lower than that of the conventional BA based on the good convergence performance for the optimisation problem. It can enrich the theoretical base of the BA as a resource for convergence performance and further optimisation analysis.

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Nächstes Kapitel Development of the Bees Algorithm Toolkit for Optimisation in LabVIEW

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Titel: Local Optimal Issue in Bees Algorithm: Markov Chain Analysis and Integration with Dynamic Particle Swarm Optimisation Algorithm
verfasst von: JianBang Liu
Mei Choo Ang
Kok Weng Ng
Jun Kit Chaw
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_3

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