A novel swarm intelligence optimization approach: sparrow search algorithm

2020/01/01 by Jiankai Xue, Bo Shen · 8 citations
Computer Science · Engineering · #Artificial Immune Systems Applications #Evolutionary Algorithms and Applications #Metaheuristic Optimization Algorithms Research

paper · pdf · doi:10.1080/21642583.2019.1708830

openalex publication_date 2020/01/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/31

Abstract

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.

Citations

• GSA: A Gravitational Search Algorithm
• Genetic Algorithms

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