论文标题
贝叶斯优化在飞机设计的工业MDO框架上有效地应用
An efficient application of Bayesian optimization to an industrial MDO framework for aircraft design
论文作者
论文摘要
在庞巴迪航空开发的多层次，多学科和多保真优化框架已显示出很好的结果，以探索高效和竞争性的飞机配置。该优化框架已在Isight软件中开发出来，后者提供了一组现成的优化器。不幸的是，就工业环境的要求而言，ISIGHT优化器所需的计算工作可能会令人难以置信。在本文中，受约束的贝叶斯优化优化器（即超高效的全局优化与专家的混合物）用于减少优化计算工作。与两个流行的Isight优化器相比，获得的结果显示出显着改善。在轰炸机研究飞机配置研究案例中，证明了经过测试的约束贝叶斯优化求解器的功能。
The multi-level, multi-disciplinary and multi-fidelity optimization framework developed at Bombardier Aviation has shown great results to explore efficient and competitive aircraft configurations. This optimization framework has been developed within the Isight software, the latter offers a set of ready-to-use optimizers. Unfortunately, the computational effort required by the Isight optimizers can be prohibitive with respect to the requirements of an industrial context. In this paper, a constrained Bayesian optimization optimizer, namely the super efficient global optimization with mixture of experts, is used to reduce the optimization computational effort. The obtained results showed significant improvements compared to two of the popular Isight optimizers. The capabilities of the tested constrained Bayesian optimization solver are demonstrated on Bombardier research aircraft configuration study cases.
