Towards demand-driven optimization algorithms in electromagnetic engineering (invited paper)

Maria Kovaleva; David Bulger; Karu P. Esselle

doi:10.1109/ICCEM47450.2020.9219432

Towards demand-driven optimization algorithms in electromagnetic engineering (invited paper)

Maria Kovaleva, David Bulger, Karu P. Esselle

School of Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

Abstract

With the increasing popularity of optimization algorithms in electromagnetic engineering, it is clear that mixed-variable design problems prevail. This paper shows that the Cross-Entropy (CE) optimization method is intrinsically versatile to handle these and other types of problems. We provide implementation details of two antenna examples optimized by the CE method to demonstrate its elegance and efficiency.

Original language	English
Title of host publication	Proceedings of the 2020 IEEE International Conference on Computational Electromagnetics (ICCEM 2020)
Place of Publication	Piscataway, NJ
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	95-96
Number of pages	2
ISBN (Electronic)	9781728134482, 9781728134475
ISBN (Print)	9781728134499
DOIs	https://doi.org/10.1109/ICCEM47450.2020.9219432
Publication status	Published - 2020
Event	6th IEEE International Conference on Computational Electromagnetics, ICCEM 2020 - Singapore, Singapore Duration: 24 Aug 2020 → 26 Aug 2020

Conference

Conference	6th IEEE International Conference on Computational Electromagnetics, ICCEM 2020
Country/Territory	Singapore
City	Singapore
Period	24/08/20 → 26/08/20

Access to Document

10.1109/ICCEM47450.2020.9219432

Cite this

@inproceedings{23eeea291dd24f2aa068428dcec10d7d,

title = "Towards demand-driven optimization algorithms in electromagnetic engineering (invited paper)",

abstract = "With the increasing popularity of optimization algorithms in electromagnetic engineering, it is clear that mixed-variable design problems prevail. This paper shows that the Cross-Entropy (CE) optimization method is intrinsically versatile to handle these and other types of problems. We provide implementation details of two antenna examples optimized by the CE method to demonstrate its elegance and efficiency. ",

author = "Maria Kovaleva and David Bulger and Esselle, {Karu P.}",

year = "2020",

doi = "10.1109/ICCEM47450.2020.9219432",

language = "English",

isbn = "9781728134499",

pages = "95--96",

booktitle = "Proceedings of the 2020 IEEE International Conference on Computational Electromagnetics (ICCEM 2020)",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

note = "6th IEEE International Conference on Computational Electromagnetics, ICCEM 2020 ; Conference date: 24-08-2020 Through 26-08-2020",

}

Kovaleva, M, Bulger, D & Esselle, KP 2020, Towards demand-driven optimization algorithms in electromagnetic engineering (invited paper). in Proceedings of the 2020 IEEE International Conference on Computational Electromagnetics (ICCEM 2020). Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, pp. 95-96, 6th IEEE International Conference on Computational Electromagnetics, ICCEM 2020, Singapore, Singapore, 24/08/20. https://doi.org/10.1109/ICCEM47450.2020.9219432

Towards demand-driven optimization algorithms in electromagnetic engineering (invited paper). / Kovaleva, Maria; Bulger, David; Esselle, Karu P.
Proceedings of the 2020 IEEE International Conference on Computational Electromagnetics (ICCEM 2020). Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2020. p. 95-96.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

TY - GEN

T1 - Towards demand-driven optimization algorithms in electromagnetic engineering (invited paper)

AU - Kovaleva, Maria

AU - Bulger, David

AU - Esselle, Karu P.

PY - 2020

Y1 - 2020

N2 - With the increasing popularity of optimization algorithms in electromagnetic engineering, it is clear that mixed-variable design problems prevail. This paper shows that the Cross-Entropy (CE) optimization method is intrinsically versatile to handle these and other types of problems. We provide implementation details of two antenna examples optimized by the CE method to demonstrate its elegance and efficiency.

AB - With the increasing popularity of optimization algorithms in electromagnetic engineering, it is clear that mixed-variable design problems prevail. This paper shows that the Cross-Entropy (CE) optimization method is intrinsically versatile to handle these and other types of problems. We provide implementation details of two antenna examples optimized by the CE method to demonstrate its elegance and efficiency.

UR - http://www.scopus.com/inward/record.url?scp=85095611272&partnerID=8YFLogxK

U2 - 10.1109/ICCEM47450.2020.9219432

DO - 10.1109/ICCEM47450.2020.9219432

M3 - Conference proceeding contribution

AN - SCOPUS:85095611272

SN - 9781728134499

SP - 95

EP - 96

BT - Proceedings of the 2020 IEEE International Conference on Computational Electromagnetics (ICCEM 2020)

PB - Institute of Electrical and Electronics Engineers (IEEE)

CY - Piscataway, NJ

T2 - 6th IEEE International Conference on Computational Electromagnetics, ICCEM 2020

Y2 - 24 August 2020 through 26 August 2020

ER -

Towards demand-driven optimization algorithms in electromagnetic engineering (invited paper)

Abstract

Conference

Access to Document

Other files and links

Fingerprint

Cite this