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A novel swarm intelligence optimization approach: sparrow search algorithm
Ist Teil von
Systems science & control engineering, 2020-01, Vol.8 (1), p.22-34
Ort / Verlag
Macclesfield: Taylor & Francis
Erscheinungsjahr
2020
Quelle
EZB Electronic Journals Library
Beschreibungen/Notizen
In this paper, a novel swarm optimization approach, namely sparrow search algorithm (SSA), is proposed inspired by the group wisdom, foraging and anti-predation behaviours of sparrows. Experiments on 19 benchmark functions are conducted to test the performance of the SSA and its performance is compared with other algorithms such as grey wolf optimizer (GWO), gravitational search algorithm (GSA), and particle swarm optimization (PSO). Simulation results show that the proposed SSA is superior over GWO, PSO and GSA in terms of accuracy, convergence speed, stability and robustness. Finally, the effectiveness of the proposed SSA is demonstrated in two practical engineering examples.