期刊
EUROPEAN JOURNAL OF COMPUTATIONAL MECHANICS
卷 17, 期 1-2, 页码 103-126出版社
TAYLOR & FRANCIS LTD
DOI: 10.3166/REMN.17.103-126
关键词
aerodynamics; computational fluid dynamics; adjoint methods; genetic algorithms
类别
A genetic algorithm is compared with a gradient-based (adjoint) algorithm in the context of several aerodynamic shape optimization problems. The examples include singlepoint and multipoint optimization problems, as well as the computation of a Pareto front. The results demonstrate that both algorithms converge reliably to the same optimum. Depending on the nature of the problem, the number of design variables, and the degree of convergence, the genetic algorithm requires from 5 to 200 times as many function evaluations as the gradientbased algorithm.
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