A novel swarm intelligence optimization approach: sparrow search algorithm 论文
2020Systems Science & Control Engineering引用 3566顶会
Metaheuristic Optimization Algorithms ResearchEvolutionary Algorithms and ApplicationsArtificial Immune Systems Applications
详细信息
- 发表期刊/会议
- Systems Science & Control Engineering
- 发表日期
- 2020-01-01
- 发表年份
- 2020
关键词
Metaheuristic Optimization Algorithms ResearchEvolutionary Algorithms and ApplicationsArtificial Immune Systems Applications
摘要
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.