A new bio-inspired optimisation algorithm: Bird Swarm Algorithm. Issue 4 (3rd July 2016)

• Record Type: Journal Article
• Authors: Meng, Xian-Bing; Gao, X.Z.; Lu, Lihua; Liu, Yu; Zhang, Hengzhen
• Is Part Of: Journal of experimental & theoretical artificial intelligence. Volume 28:Issue 4(2016)
• Page Start: 673
• Page End: 687
• Publication Date: 2016-07-03
• Subjects: bird swarms -- swarm intelligence -- social behaviours -- social interactions -- Bird Swarm Algorithm -- optimisation; Artificial intelligence -- Periodicals; 006.3
• DOI: 10.1080/0952813X.2015.1042530
• Languages: English
• ISSNs: 0952-813X

Abstract

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.