Journal
JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE
Volume 28, Issue 4, Pages 673-687Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/0952813X.2015.1042530
Keywords
bird swarms; swarm intelligence; social behaviours; social interactions; Bird Swarm Algorithm; optimisation
Categories
Funding
- New Academic Staff Program of Shanghai Maritime University [GK2013089]
Ask authors/readers for more resources
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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available