A new bio-inspired optimisation algorithm: Bird Swarm Algorithm

Xian Bing Meng*, X. Z. Gao, Lihua Lu, Yu Liu, Hengzhen Zhang

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

169 Citations (Scopus)

Abstract

A new bio-inspired algorithm, namely Bird Swarm Algorithm (BSA), is proposed for solving optimisation applications. BSA is based on the swarm intelligence extracted from the social behaviours and social interactions in bird swarms. Birds mainly have three kinds of behaviours: foraging behaviour, vigilance behaviour and flight behaviour. Birds may forage for food and escape from the predators by the social interactions to obtain a high chance of survival. By modelling these social behaviours, social interactions and the related swarm intelligence, four search strategies associated with five simplified rules are formulated in BSA. Simulations and comparisons based on eighteen benchmark problems demonstrate the effectiveness, superiority and stability of BSA. Some proposals for future research about BSA are also discussed.

Original languageEnglish
Pages (from-to)673-687
Number of pages15
JournalJOURNAL OF EXPERIMENTAL AND THEORETICAL ARTIFICIAL INTELLIGENCE
Volume28
Issue number4
DOIs
Publication statusPublished - 3 Jul 2016
MoE publication typeA1 Journal article-refereed

Keywords

  • Bird Swarm Algorithm
  • bird swarms
  • optimisation
  • social behaviours
  • social interactions
  • swarm intelligence

Fingerprint Dive into the research topics of 'A new bio-inspired optimisation algorithm: Bird Swarm Algorithm'. Together they form a unique fingerprint.

Cite this