Multiobjective genetic algorithm applied to aerodynamic design ofcascade airfoils
Obayashi, S.; Tsukahara, T.; Nakamura, T.
Industrial Electronics, IEEE Transactions on
Volume 47, Issue 1, Feb 2000 Page(s):211 - 216
Digital Object Identifier   10.1109/41.824144
Summary:A multiobjective genetic algorithm (GA) based on Fonseca-Fleming's Pareto-based ranking and fitness-sharing techniques has been applied to aerodynamic shape optimization of cascade airfoil design. Airfoil performance is evaluated by a Navier-Stokes code. Evaluation of GA population is parallelized on the Numerical Wind Tunnel, a parallel vector machine. The present multiobjective design seeks high pressure rise, high flow turning angle, and low total pressure loss at a low Mach number. Pareto solutions that perform better than existing control diffusion airfoils were obtained

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