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Diversity and Mechanisms in Swarm Intelligence

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  • Xin-She Yang

    (School of Science and Technology, Middlesex University London, London, UK)

Abstract

Swarm intelligence based algorithms such as particle swarm optimization have become popular in the last two decades. Various new algorithms such as cuckoo search and bat algorithm also show promising efficiency. In all these algorithms, it is essential to maintain the balance of exploration and exploitation by controlling directly and indirectly the diversity of the population. Different algorithms may use different mechanisms to control such diversity. In this review paper, the author reviews and analyzes the roles of diversity and relevant mechanisms in swarm intelligence. The author also discuss parameter tuning and parameter control. In addition, the author highlights some key open questions in swarm intelligence.

Suggested Citation

  • Xin-She Yang, 2014. "Diversity and Mechanisms in Swarm Intelligence," International Journal of Swarm Intelligence Research (IJSIR), IGI Global, vol. 5(2), pages 1-12, April.
    • Handle: RePEc:igg:jsir00:v:5:y:2014:i:2:p:1-12
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    Cited by:

    1. Yi Yu & Yonggang Wu & Binqi Hu & Xinglong Liu, 2018. "An enhanced artificial bee colony algorithm (EABC) for solving dispatching of hydro-thermal system (DHTS) problem," PLOS ONE, Public Library of Science, vol. 13(1), pages 1-19, January.

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