An improved TLBO based memetic algorithm for aerodynamic shape optimization. (January 2017)

• Record Type: Journal Article
• Authors: Qu, Xinghua; Zhang, Ran; Liu, Bo; Li, Huifeng
• Is Part Of: Engineering applications of artificial intelligence. Volume 57(2016:Sep.)
• Page Start: 1
• Page End: 15
• Publication Date: 2017-01
• Subjects: Aerodynamic shape optimization -- Teaching-Learning based optimization -- Memetic algorithm; Engineering -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Ingénierie -- Informatique -- Périodiques; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; Artificial intelligence; Engineering -- Data processing; Expert systems (Computer science); Periodicals; 620.00285
• DOI: 10.1016/j.engappai.2016.10.009
• Languages: English
• ISSNs: 0952-1976

Abstract

Abstract: 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.