Swarm algorithm for single- and multiobjective airfoil design optimization

Shape optimization of airfoils involves highly expensive, nonlinear objective(s) and constraint functions often with functional and slope discontinuity that limits the efficient use of gradient-based methods for its solution. Gradient-based methods are not capable of generating a set of pareto solutions as required in multiobjective problems as they work with a single solution and improve it through successive iterations. Population-based, zero-order, stochastic optimization methods are therefore an attractive choice for shape optimization problems as they are easy to implement and effective for highly nonlinear problems. We present a swarm algorithm that is applicable for optimization problems in general, but is here explored for airfoil design optimization studies

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