An Efficient Method for Antenna Design Optimization Based on Evolutionary Computation and Machine Learning Techniques
In recent years, various methods from the evolutionary computation (EC) field have been applied to electromagnetic (EM) design problems and have shown promising results. However, due to the high computational cost of the EM simulations, the efficiency of directly using evolutionary algorithms is oft...
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| Vydané v: | IEEE transactions on antennas and propagation Ročník 62; číslo 1; s. 7 - 18 |
|---|---|
| Hlavní autori: | , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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New York, NY
IEEE
01.01.2014
Institute of Electrical and Electronics Engineers |
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| ISSN: | 0018-926X, 1558-2221 |
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| Abstract | In recent years, various methods from the evolutionary computation (EC) field have been applied to electromagnetic (EM) design problems and have shown promising results. However, due to the high computational cost of the EM simulations, the efficiency of directly using evolutionary algorithms is often very low (e.g., several weeks' optimization time), which limits the application of these methods for many industrial applications. To address this problem, a new method, called surrogate model assisted differential evolution for antenna synthesis (SADEA), is presented in this paper. The key ideas are: (1) A Gaussian Process (GP) surrogate model is constructed on-line to predict the performances of the candidate designs, saving a lot of computationally expensive EM simulations. (2) A novel surrogate model-aware evolutionary search mechanism is proposed, directing effective global search even when a traditional high-quality surrogate model is not available. Three complex antennas and two mathematical benchmark problems are selected as examples. Compared with the widely used differential evolution and particle swarm optimization, SADEA can obtain comparable results, but achieves a 3 to 7 times speed enhancement for antenna design optimization. |
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| AbstractList | In recent years, various methods from the evolutionary computation (EC) field have been applied to electromagnetic (EM) design problems and have shown promising results. However, due to the high computational cost of the EM simulations, the efficiency of directly using evolutionary algorithms is often very low (e.g., several weeks' optimization time), which limits the application of these methods for many industrial applications. To address this problem, a new method, called surrogate model assisted differential evolution for antenna synthesis (SADEA), is presented in this paper. The key ideas are: (1) A Gaussian Process (GP) surrogate model is constructed on-line to predict the performances of the candidate designs, saving a lot of computationally expensive EM simulations. (2) A novel surrogate model-aware evolutionary search mechanism is proposed, directing effective global search even when a traditional high-quality surrogate model is not available. Three complex antennas and two mathematical benchmark problems are selected as examples. Compared with the widely used differential evolution and particle swarm optimization, SADEA can obtain comparable results, but achieves a 3 to 7 times speed enhancement for antenna design optimization. |
| Author | Excell, Peter Aliakbarian, Hadi Gielen, Georges Vandenbosch, Guy A. E. Bo Liu Zhongkun Ma |
| Author_xml | – sequence: 1 surname: Bo Liu fullname: Bo Liu email: b.liu@glyndwr.ac.uk organization: Dept. of Comput., Glyndwr Univ., Wrexham, UK – sequence: 2 givenname: Hadi surname: Aliakbarian fullname: Aliakbarian, Hadi email: Hadi.Aliakbarian@esat.kuleuven.be organization: ESAT, Katholieke Univ. Leuven, Leuven, Belgium – sequence: 3 surname: Zhongkun Ma fullname: Zhongkun Ma email: Zhongkun.Ma@esat.kuleuven.be organization: ESAT, Katholieke Univ. Leuven, Leuven, Belgium – sequence: 4 givenname: Guy A. E. surname: Vandenbosch fullname: Vandenbosch, Guy A. E. email: Guy.Vandenbosch@esat.kuleuven.be organization: ESAT, Katholieke Univ. Leuven, Leuven, Belgium – sequence: 5 givenname: Georges surname: Gielen fullname: Gielen, Georges email: Georges.Gielen@esat.kuleuven.be organization: ESAT, Katholieke Univ. Leuven, Leuven, Belgium – sequence: 6 givenname: Peter surname: Excell fullname: Excell, Peter email: p.excell@glyndwr.ac.uk organization: Inst. of Arts, Sci. & Technol., Glyndwr Univ., Wrexham, UK |
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| Cites_doi | 10.1109/CEC.2006.1688312 10.1109/8.155746 10.1023/A:1008306431147 10.1109/TMAG.2009.2012695 10.1109/AICI.2009.307 10.1109/TAP.2007.891552 10.1007/978-1-4757-3799-8 10.1145/2228360.2228457 10.1109/TEVC.2002.800884 10.1109/TMTT.2003.820891 10.1109/TAP.2007.893400 10.1109/TAP.2010.2103029 10.1109/TAP.2011.2109678 10.1109/TAP.2011.2109350 10.1109/TAP.2007.891306 10.1109/APS.2010.5561993 10.1109/TEVC.2005.851274 10.1007/s00500-003-0328-5 10.1109/JSSC.2007.900236 10.1109/TAP.2012.2194685 10.1080/00401706.1987.10488205 10.1029/2010JA016375 10.1109/TAP.2004.823969 10.1109/TEVC.2009.2027359 10.1109/TMTT.2003.820904 10.1109/TCAD.2011.2162067 10.1109/TSMCC.2004.841917 10.1109/MAP.2011.5773566 10.1109/TSMCC.2005.855506 10.1109/TAP.2008.2009775 10.1109/TED.2005.850668 10.1109/TEVC.2005.859463 10.1109/8.805906 |
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| Keywords | Performance evaluation Electromagnetism Evolutionary algorithm Industrial application Evolutionary computation Global optimum Antenna design optimization Computational complexity Particle swarm optimization efficient global optimization differential evolution Gaussian process Biomimetics Simulation surrogate model assisted evolutionary algorithm On line processing Artificial intelligence expensive black-box optimization Antenna Antenna synthesis |
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| References | ref35 ref13 price (ref4) 2005 ref34 ref37 ref15 ref36 ref14 ref30 ref33 ref11 ref32 ref10 ma (ref40) 2012; 21 ref2 ref1 ref17 ref38 ref16 ref19 ref18 gorissen (ref31) 2010; 11 dennis (ref23) 1997 clerc (ref5) 2010 koziel (ref12) 2010 emmerich (ref25) 2006; 10 ref24 santner (ref20) 2003 ref26 volski (ref39) 2004 ref22 ref21 ref28 ref27 ref29 ref8 ref7 ref9 ref3 ref6 |
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| SubjectTerms | Antenna design optimization antenna synthesis Antennas Applied classical electromagnetism Applied sciences Computational modeling differential evolution efficient global optimization Electromagnetic wave propagation, radiowave propagation Electromagnetism; electron and ion optics Exact sciences and technology expensive black-box optimization Fundamental areas of phenomenology (including applications) Gaussian process Mathematical model Optimization Physics Predictive models Radiocommunications surrogate model assisted evolutionary algorithm Telecommunications Telecommunications and information theory Training data |
| Title | An Efficient Method for Antenna Design Optimization Based on Evolutionary Computation and Machine Learning Techniques |
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