An improved TLBO based memetic algorithm for aerodynamic shape optimization

Aerodynamic shape optimization (ASO) for aircraft is the focus of concern as well as the subject of substantial research issue in aerospace engineering. This paper proposes a novel TLBO (teaching-learning based optimization based) memetic algorithm (TLBO-MA) for optimizing the aerodynamic shape. In the proposed TLBO-MA, an adaptive teaching factor, conservation of information inspired operator and multi-meme learning are incorporated to enhance the searching behavior of standard TLBO. Simulation based on well-known benchmarks and ASO for HTV-2 prototype demonstrates the efficiency of the proposed TLBO-MA.

Authors

• Xinghua Qu Bytedance(Seed), Singapore
• Ran Zhang Computer Network Information Center, Chinese Academy of Science; University of Chinese Academy of Sciences
• Bo Liu Peking University
• Huifeng Li

Keywords

• Aerodynamic shape optimization
• Teaching-Learning based optimization
• Memetic algorithm