کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6874553 687526 2015 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Efficient knowledge-based optimization of expensive computational models using adaptive response correction
ترجمه فارسی عنوان
بهینه سازی کارآمد مبتنی بر دانش از مدل های محاسباتی گران با استفاده از تصحیح پاسخ انطباقی
کلمات کلیدی
مدل سازی جایگزین، بهینه سازی مبتنی بر جایگزین، اتوماسیون طراحی، تصحیح پاسخ سازگار، مهندسی مایکروویو، طراحی آنتن، مدل سازی دینامیک سیالات، بهینه سازی شکل آیرودینامیک،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نظریه محاسباتی و ریاضیات
چکیده انگلیسی
Computer simulation has become an indispensable tool in engineering design as they allow an accurate evaluation of the system performance. This is critical in order to carry out the design process in a reliable manner without costly prototyping and physical measurements. However, high-fidelity computer simulations are computationally expensive. This turns to be a fundamental bottleneck when it comes to design automation using numerical optimization techniques. In particular, direct optimization of simulation models, typically, requires a large number of model evaluations, which may be impractical or even infeasible in a reasonable timeframe. Possibly the most promising approach to alleviate this difficulty is surrogate-based optimization (SBO), where direct optimization of expensive models is replaced by an iterative enhancement and re-optimization of fast surrogate models. While a large variety of surrogate modeling and optimization are available, the methods exploiting the so-called physics-based surrogates seem to be the most efficient ones because the knowledge about the system of interest embedded in the underlying (often simulation-based) low-fidelity model ensures good generalization of the surrogate and a rapid convergence of the SBO algorithm. In this paper, we review a specific technique of this class, that is, the adaptive response correction (ARC). We discuss the formulation of the method, its limitations and generalizations, as well as illustrate its application for solving problems in various areas, including microwave engineering, antenna design, and aerodynamic shape optimization.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Computational Science - Volume 11, November 2015, Pages 1-11
نویسندگان
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