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Diversifying search in bee algorithms for numerical optimisation

Düg̃enci, Muharrem; Aydin, Mehmet Emin


Muharrem Düg̃enci

Mehmet Aydin
Senior Lecturer in Networks and Mobile Computing


N.T. Nguyen

E. Pimenidis

Z. Khan

B. Trawiński


Swarm intelligence offers useful instruments for developing collective behaviours to solve complex, ill-structured and large-scale problems. Efficiency in collective behaviours depends on how to harmonise the individual contributions so that a complementary collective effort can be achieved to offer a useful solution. The harmonisation helps blend diversification and intensification suitably towards efficient collective behaviours. In this study, two renown honeybees-inspired algorithms were analysed with respect to the balance of diversification and intensification and a hybrid algorithm is proposed to improve the efficiency accordingly. The proposed hybrid algorithm was tested with solving well-known highly dimensional numerical optimisation (benchmark) problems. Consequently, the proposed hybrid algorithm has demonstrated outperforming the two original bee algorithms in solving hard numerical optimisation benchmarks.

Journal Article Type Article
Start Date Sep 5, 2018
Publication Date Aug 27, 2018
Journal Lecture Notes in Computer Science
Print ISSN 0302-9743
Publisher Springer Verlag
Peer Reviewed Peer Reviewed
Volume 11056
Pages 132-144
Book Title Computational Collective Intelligence
ISBN 9783319984452
Institution Citation Düg̃enci, M., & Aydin, M. E. (2018). Diversifying search in bee algorithms for numerical optimisation. Lecture Notes in Artificial Intelligence, 11056, 132-144.
Keywords swarm intelligence, numerical optimisation, bee-inspired algorithms, diversification and intensification
Publisher URL
Additional Information Additional Information : The final authenticated version is available online at
Title of Conference or Conference Proceedings : 10th International Conference, ICCCI 2018, Bristol, UK


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