关键词: 粒子群优化, 人工鱼群算法, 社会模型, 搜索效率, 气动优化设计

Abstract: A universal strategy named the social model is developed and a new algorithm named improved particle swarm optimization based on social model (IPSOSM) algorithm is proposed in order to improve the searching efficiency of an optimization system. The social model is first analyzed and, with the guidance of the social model theory, the collective action which belongs to artificial fish swarm algorithm (AFSA) is then introduced into particle swarm optimization (PSO) algorithm. This enlarges the best information of particle swarm and improves the ability of communication among the particle swarm, which helps get rid of strapping into a local minimum. Function test results show that the IPSOSM algorithm has much better optimazing ability than the PSO algorithm. The IPSOSM algorithm is applied to an airfoil aerodynamic design and a wing aerodynamic design and satisfactory optimal results are obtained, which proves the simplicity and efficiency of the social model.

Key words: particle swarm optimization, artificial fish swarm algorithm, social model, searching efficiency, aerodynamic optimization design