Diversifying Search in Bee Algorithms for Numerical Optimisation
Yazarlar (2)
Prof. Dr. Muharrem DÜĞENCİ Karabük Üniversitesi, Türkiye
Mehmet Emin Aydın University Of The West Of England, İngiltere
| Bildiri Türü | Tebliğ/Bildiri | Bildiri Dili | İngilizce |
| Bildiri Alt Türü | Tam Metin Olarak Yayınlanan Tebliğ (Uluslararası Kongre/Sempozyum) | ||
| Bildiri Niteliği | Web of Science Kapsamındaki Kongre/Sempozyum | ||
| DOI Numarası | 10.1007/978-3-319-98446-9_13 | ||
| Kongre Adı | 10. International Conference on Computational Collective Intelligence | ||
| Kongre Tarihi | 05-09-2018 / 07-09-2018 | ||
| Basıldığı Ülke | Basıldığı Şehir | ||
| Bildiri Linki | http://link.springer.com/10.1007/978-3-319-98446-9_13 | ||
| UAK Araştırma Alanları |
Veri Madenciliği
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| Özet |
| 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 … |
| Anahtar Kelimeler |
| Bee-inspired algorithms | Diversification and intensification | Numerical optimisation | Swarm intelligence |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Web of Science | 1 |
| Scopus | 3 |
| Google Scholar | 3 |