Designing airfoils using a reference point based evolutionary many-objective particle swarm optimization algorithm

— In this paper, we illustrate the use of a reference point based many-objective particle swarm optimization algorithm to optimize low-speed airfoil aerodynamic designs. Our framework combines a flexible airfoil parameterization scheme and a computational flow solver in the evaluation of particles. Each particle, which represents a set of decision variables, is passed through this framework to construct and evaluate the airfoils and assign fitness. We used the baseline NLF0416 airfoil to obtain aspiration values, which are used to define the reference point. This reference point guides the swarm towards the preferred region of the objective landscape to find solutions of interest to the decision maker. The proficiency of the algorithm is highlighted by monitoring convergence and spread of solution using a hyper-volume calculation scheme suitable for user-preference based evolutionary many-objective algorithms. The results comparing the reference point based approach with a stan...

• Type: Conference
• Year: 2010
• Where: CEC
• Authors: Upali K. Wickramasinghe, Robert Carrese, Xiaodong Li
• Keywords: Airfoil, Algorithm, Artificial Intelligence, CEC 2010, Reference Point