Sequential Domain Patching for Computationally Feasible Multi-Objective Optimization of Expensive Electromagnetic Simulation Models

被引:1
|
作者
Bekasiewicz, Adrian [1 ,2 ,3 ]
Koziel, Slawomir [1 ,3 ,4 ]
Leifsson, Leifur [5 ]
机构
[1] Reykjavik Univ, Engn Optimizat & Modeling Ctr, Sch Sci & Engn, Reykjavik, Iceland
[2] Reykjavik Univ, Fac Elect Telecommun & Informat, Reykjavik, Iceland
[3] Gdansk Univ Technol, Engn Optimizat & Modeling Ctr, Sch Sci & Engn, Gdansk, Poland
[4] Gdansk Univ Technol, Fac Elect Telecommun & Informat, Gdansk, Poland
[5] Iowa State Univ, Dept Aerosp Engn, Ames, IA USA
关键词
multi-objective optimization; sequential domain patching; surrogate modeling; antenna design; impedance transformer design; ANTENNA DESIGN;
D O I
10.1016/j.procs.2016.05.414
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
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.
引用
收藏
页码:1093 / 1102
页数:10
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