Liu Ying, Cheng Qingsha S, Koziel Slawomir
Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen 518055, China.
School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150001, China.
Sensors (Basel). 2019 Jul 11;19(14):3065. doi: 10.3390/s19143065.
In this article, a generalized sequential domain patching (GSDP) method for efficient multi-objective optimization based on electromagnetics (EM) simulation is proposed. The GSDP method allowing fast searching for Pareto fronts for two and three objectives is elaborated in detail in this paper. The GSDP method is compared with the NSGA-II method using multi-objective problems in the DTLZ series, and the results show the GSDP method saved computational cost by more than 85% compared to NSGA-II method. A diversity comparison indicator (DCI) is used to evaluate approximate Pareto fronts. The comparison results show the diversity performance of GSDP is better than that of NSGA-II in most cases. We demonstrate the proposed GSDP method using a practical multi-objective design example of EM-based UWB antenna for IoT applications.
本文提出了一种基于电磁（EM）仿真的高效多目标优化广义序贯域修补（GSDP）方法。本文详细阐述了允许快速搜索两个和三个目标的帕累托前沿的GSDP方法。将GSDP方法与使用DTLZ系列多目标问题的NSGA-II方法进行了比较，结果表明，与NSGA-II方法相比，GSDP方法节省了超过85%的计算成本。使用多样性比较指标（DCI）来评估近似帕累托前沿。比较结果表明，在大多数情况下，GSDP的多样性性能优于NSGA-II。我们通过一个基于EM的物联网应用超宽带天线的实际多目标设计示例，展示了所提出的GSDP方法。
