A new bio-inspired optimisation algorithm: Bird Swarm Algorithm

• Published in: Journal of experimental & theoretical artificial intelligence Vol. 28; no. 4; pp. 673 - 687
• Main Authors: Meng, Xian-Bing, Gao, X.Z., Lu, Lihua, Liu, Yu, Zhang, Hengzhen
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 03-07-2016; Taylor & Francis Ltd
• Subjects: Algorithms; Animal behavior; Artificial intelligence; Bird Swarm Algorithm; bird swarms; Birds; Forages; optimisation; Optimization; Optimization algorithms; Proposals; Searching; Social aspects; social behaviours; social interactions; Swarm intelligence
• ISSN: 0952-813X; 1362-3079
• DOI: 10.1080/0952813X.2015.1042530

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.