摘要
现代启发式智能算法存在全局与局部搜索能力的平衡问题,针对此问题,采用双种群进化策略和信息交流机制,提出一种基于粒子群算法和人工蜂群算法相结合的新型混合优化算法——MABCPSO,并分别进行函数测试和翼型的气动优化设计验证。结果表明:MABCPSO新型混合优化算法具有更好的寻优能力,相比粒子群算法和人工蜂群算法,该算法能以更少的进化代数分别提高1.7%和2.2%的减阻效果。
The modern intelligent algorithm is of the balance problem of global and local search ability. Because of this, a new hybrid optimization algorithm based on particle swarm optimization and artificial bee colony algorithm（it is called hybrid method of ABC and PSO--MABCPSO） is proposed, which is based on the two-group evolutionary strategy and information sharing mechanism, and the function tests and airfoil aerodynamic optimization design validation are carried out respectively. The results show that MABCPSO new hybrid optimization algorithm has better searching ability, which can improve the drag reduction effect by 1.7% and 2.2% with less evolutionary algebra than particle swarm optimization（PSO） and artificial bee colony algorithm（ABC） algorithm respectively.
出处
《航空工程进展》
CSCD
2017年第2期182-189,共8页
Advances in Aeronautical Science and Engineering
关键词
粒子群算法
人工蜂群算法
混合算法
气动优化设计
particle swarm optimization（PSO）
artificial bee colony algorithm（ABC）
hybrid algorithm
aerodynamic optimization design
