Swarm intelligence-based optimisation algorithms: an overview and future research issues
by Jinqiang Hu; Husheng Wu; Bin Zhong; Renbin Xiao
International Journal of Automation and Control (IJAAC), Vol. 14, No. 5/6, 2020

Abstract: Swarm intelligence-based optimisation algorithms, inspired by the collective intelligent behaviours of biology groups, have been widely recognised as efficient optimisers for many complex problems, e.g., dynamic optimisation problems, large-scale optimisation problems and many-objective optimisation problems. Swarm intelligence-based algorithms are the generic concepts to represent a range of metaheuristics with population-based iterative process, guided random search and parallel processing. This paper conducts an in-depth analysis of universality and difference of existing swarm intelligence-based algorithms. It also provides a systematical survey of some well-known algorithms. In addition, the expected research issues such as theoretical analysis, hybridisation strategy and complex problems optimisation are discussed thoroughly to inspire future study and more extensive applications.

Online publication date: Mon, 05-Oct-2020

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