دانلود مقاله ISI انگلیسی شماره 78405
ترجمه فارسی عنوان مقاله

بهینه سازی توزیع دامنه برای بهینه سازی چند هدفه محاسباتی مدل های شبیه سازی الکترومغناطیسی گران قیمت

عنوان انگلیسی
Sequential Domain Patching for Computationally Feasible Multi-objective Optimization of Expensive Electromagnetic Simulation Models ☆
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
78405 2016 10 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Procedia Computer Science, Volume 80, 2016, Pages 1093–1102

ترجمه کلمات کلیدی
بهینه سازی چند هدفه پچ دامنه تکراری مدل سازی جایگزین، طراحی آنتن، طراحی ترانسفورماتور امپدانس
کلمات کلیدی انگلیسی
multi-objective optimization; sequential domain patching; surrogate modeling; antenna design; impedance transformer design ;

چکیده انگلیسی

In this paper, we discuss a simple and efficient technique for multi-objective design optimization of multi-parameter microwave and antenna structures. Our method exploits a stencil-based approach for identification of the Pareto front that does not rely on population-based metaheuristic algorithms, typically used for this purpose. The optimization procedure is realized in two steps. Initially, the initial Pareto-optimal set representing the best possible trade-offs between conflicting objectives is obtained using low-fidelity representation (coarsely-discretized EM model simulations) of the structure at hand. This is realized by sequential construction and relocation of small design space segments (patches) in order to create a path connecting the extreme Pareto front designs identified beforehand. In the second step, the Pareto set is refined to yield the optimal designs at the level of the high-fidelity electromagnetic (EM) model. The appropriate number of patches is determined automatically. The approach is validated by means of two multi-parameter design examples: a compact impedance transformer, and an ultra-wideband monopole antenna. Superiority of the patching method over the state-of-the-art multi-objective optimization techniques is demonstrated in terms of the computational cost of the design process.