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ONERA的基于代理的优化：最近的一些例子

Surrogate-Based Optimization at ONERA: Some Recent Examples
课程网址: http://videolectures.net/mla09_meunier_sbo/  
主讲教师: Mickaël Meunier
开课单位: 法国航空航天实验室
开课时间: 2009-07-20
课程语种: 英语
中文简介:
随着计算资源的发展和工业需求的日益复杂化，最近几年，社区的优化策略，特别是那些基于进化概念的策略，在社区中取得了越来越大的成功。实际上，它们为潜在的复杂问题提供全局聚焦最小化机会（例如，在（dis）连续状态变量的非连通搜索空间上具有多个最小值），而不依赖于目标函数梯度的计算，因此几乎保持不变完全独立于待处理问题的物理性质（分析器和优化器是两个截然不同的自治过程，因此通常是“黑盒子”命名）。    然而，基于整个范围的可能解决方案（其中，正式地，没有任何保证结果的绝对全局特征）的最优搜索通常受到其重要的计算成本的惩罚，其可以随着问题的复杂性呈指数增加（贝尔曼的维度诅咒）并且变得迅速禁止（特别是当人们处理大型配置的精确空气动力学评估时）。这一评论部分解释了基于代理的优化程序的普及，其中昂贵的分析器被优化器浏览的低保真但廉价模型所取代。    ONERA在代理优化领域一直活跃一段时间，主题范围从代理建模本身（RBF / ANN，（Co）Kriging，高阶RSM ...）到有效耦合和优化（抽样方法，细化标准） ，在线或离线实施......），适用于各种应用（多学科问题的单目标或多目标表现）。本演示文稿的目的是回顾一些最新项目中获得的一些结果，例如优化新型高扬程设计的流量控制参数。
课程简介: With the development of computational resources and the increasing complexity of industrial needs, stohastic optimization strategies, and especially those based on evolutionary concepts, have had a growing success among the community in the recent years. Indeed, they offer global-focusing minimization opportunities to potentially complex problems (e.g. with multiple minima over non-connected search spaces of (dis)continuous state variables) without relying on the computation of the objective function´s gradient, and as such remain almost completely independent on the physical nature of the problem to be treated (analyzer and optimizer are two distinct and autonomous processes to be interfaced with one another, hence the usual "black-box˝ denomination). Yet, the search of an optimum based on the entire range of possible solutions (where, formally, nothing guarantees the absolute global character of the result) is usually penalized by its important computational cost, which can increase exponentially with the complexity of the problem (Belmann´s curse of dimensionality) and become rapidly prohibitive (especially when one deals with precise aerodynamic evaluations on large configurations). This remark partly explains the popularity of surrogate-based optimization procedures, where the expensive analyzer is replaced by a low-fidelity but cheap model on which the optimizer browses. ONERA has been active on the field of surrogate optimization for some time now, with topics ranging from surrogate modeling itself (RBF/ANN, (Co)Kriging, high order RSM...) to efficient coupling and optimization (sampling methods, refinement criteria, on- or off-line implementation...), for a wide variety of applications (single or multi-objective performances of multidisciplinary problems). It is the aim of this presentation to review some of the results obtained throughout some of the most recent projects, such as the optimization of flow control parameters for novel high-lift design.
关 键 词: 目标函数梯度; 代理建模; 有效耦合
课程来源: 视频讲座网
最后编审: 2019-06-28：cjy
阅读次数: 25

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