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Swarm intelligence: past, present and future

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Abstract

Many optimization problems in science and engineering are challenging to solve, and the current trend is to use swarm intelligence (SI) and SI-based algorithms to tackle such challenging problems. Some significant developments have been made in recent years, though there are still many open problems in this area. This paper provides a short but timely analysis about SI-based algorithms and their links with self-organization. Different characteristics and properties are analyzed here from both mathematical and qualitative perspectives. Future research directions are outlined, and open questions are also highlighted.

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Authors and Affiliations

  1. School of Science and Technology, Middlesex University, London, NW4 4BT, UK

    Xin-She Yang

  2. IT & Educational Consultant, Ranchi, India

    Suash Deb

  3. Distinguished Professorial Associate, Decision Sciences and Modelling Program, Victoria University, Melbourne, Australia

    Suash Deb

  4. College of Automation, Harbin Engineering University, Harbin, China

    Yu-Xin Zhao

  5. Department of Computer and Information Sciences, University of Macau, Macau, China

    Simon Fong

  6. College of Science, Xi’an Polytechnic University, No. 19 Jinhua South Road, Xi’an, China

    Xingshi He

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  1. Xin-She Yang
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  5. Xingshi He
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Correspondence to Xin-She Yang.

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Communicated by S. Deb, T. Hanne, K.C. Wong.

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Yang, XS., Deb, S., Zhao, YX. et al. Swarm intelligence: past, present and future. Soft Comput 22, 5923–5933 (2018). https://doi.org/10.1007/s00500-017-2810-5

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