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Coupling hybrid-game strategies with particle swarm optimisation for multi-objective high lift systems design optimisation

机译:多目标高升力系统设计优化与粒子群优化的混合博弈策略耦合

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摘要

This paper investigates the High Lift System (HLS) application of complex aerodynamic design problem using Particle Swarm Optimisation (PSO) coupled to Game strategies. Two types of optimization methods are used; the first method is a standard PSO based on Pareto dominance and the second method hybridises PSO with a well-known Nash Game strategies named Hybrid-PSO. These optimization techniques are coupled to a pre/post processor GiD providing unstructured meshes during the optimisation procedure and a transonic analysis software PUMI. The computational efficiency and quality design obtained by PSO and Hybrid-PSO are compared. The numerical results for the multi-objective HLS design optimisation clearly shows the benefits of hybridising a PSO with the Nash game and makes promising the above methodology for solving other more complex multi-physics optimisation problems in Aeronautics.
机译:本文结合粒子群算法(PSO)和博弈策略,研究了复杂空气动力学设计问题在高升力系统(HLS)中的应用。使用两种类型的优化方法:第一种方法是基于Pareto优势的标准PSO,第二种方法是将PSO与众所周知的名为Hybrid-PSO的纳什博弈策略进行杂交。这些优化技术与在优化过程中提供非结构化网格的前/后处理器GiD以及跨音速分析软件PUMI耦合。比较了PSO和Hybrid-PSO获得的计算效率和质量设计。多目标HLS设计优化的数值结果清楚地显示了将PSO与Nash博弈混合的好处,并使上述方法有望解决航空领域其他更复杂的多物理场优化问题。

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