{"title":"Fast multi-objective antenna optimization using sequential patching and variable-fidelity EM models","authors":"S. Koziel, A. Bekasiewicz","doi":"10.1109/LAPC.2015.7366067","DOIUrl":null,"url":null,"abstract":"In this work, a technique for fast multi-objective design optimization of antenna structures is presented. In our approach, the initial approximation of the Pareto set representing the best possible trade-offs between conflicting design objectives is obtained by means of sequential patching of the design space. The latter is a stencil-based search that aims at creating a path that connects the extreme Pareto-optimal designs (obtained by means of single-objective optimization runs). For the sake of computational efficiency, the patching process is realized at the level of coarse-discretization EM simulation model. The final Pareto front is obtained through surrogate-based optimization, and it is reusing the EM simulation data acquired at the initial design stage. The proposed approach is demonstrated using the example of an ultrawideband monopole antenna.","PeriodicalId":339610,"journal":{"name":"2015 Loughborough Antennas & Propagation Conference (LAPC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Loughborough Antennas & Propagation Conference (LAPC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/LAPC.2015.7366067","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this work, a technique for fast multi-objective design optimization of antenna structures is presented. In our approach, the initial approximation of the Pareto set representing the best possible trade-offs between conflicting design objectives is obtained by means of sequential patching of the design space. The latter is a stencil-based search that aims at creating a path that connects the extreme Pareto-optimal designs (obtained by means of single-objective optimization runs). For the sake of computational efficiency, the patching process is realized at the level of coarse-discretization EM simulation model. The final Pareto front is obtained through surrogate-based optimization, and it is reusing the EM simulation data acquired at the initial design stage. The proposed approach is demonstrated using the example of an ultrawideband monopole antenna.