摘要
提出了一种基于细菌觅食性的改进粒子群优化算法。该算法以粒子群优化算法的社会模型为基础,添加了个体之间的交流项,丰富了粒子之间的优势信息源,增强了粒子的信息共享能力,同时,引入了细菌觅食算法中的趋化和驱散机制,使得算法能够有效地跳出局部最优。函数测试结果表明,该算法显著地提高了粒子群优化算法的寻优性能,并将该算法应用到了翼型设计之中。
A new algorithm named Improved Particle Swarm Optimization Based on Bacterial Foraging （IPSOBF） is proposed. The new algorithm is based on the social model of Particle Swarm Optimization and an extra communicating part is adopted which enlarges the best information of the particle swarm and improves the ability of communication among the particle swarm. Besides, inspired by the Bacterial Foraging Algorithm, a mechanism of chemotactic and elimination-dispersal is introduced into IPSOBF to help get rid of strapping into local minimal. Function test results show that IPSOBF algorithm has much better optimal ability than PSO algorithm. IPSOBF algorithm is also applied to the optimization of airfoil design and the result proves it has better optimal effects.
出处
《空气动力学学报》
EI
CSCD
北大核心
2012年第4期533-538,共6页
Acta Aerodynamica Sinica
基金
西北工业大学翱翔之星计划资助
国家自然科学基金(11172242)
关键词
粒子群优化算法
细菌觅食算法
社会模型
翼型设计
particle swarm optimization
bacterial foraging algorithm
social model
airfoil design
