Multidisciplinary design optimization of aircraft wing planform based on evolutionary algorithms

Examines the evolutionary approach for aircraft design optimization. Several niching and elitist models are first applied to multiple-objective genetic algorithms (MOGAs). Numerical results suggest that the combination of the fitness sharing and the best-N selection leads to the best performance. The resulting MOGA is then applied to multidisciplinary design optimization problems of transonic and supersonic wing planform shapes. The results confirm the feasibility of the present approach.

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