Towards Demand-Driven Optimization Algorithms in Electromagnetic Engineering (Invited Paper)

Kovaleva, M; Bulger, D; Esselle, KP

Towards Demand-Driven Optimization Algorithms in Electromagnetic Engineering (Invited Paper)

Kovaleva, M Bulger, D Esselle, KP

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Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: Proceedings of the 2020 IEEE International Conference on Computational Electromagnetics, ICCEM 2020, 2020, 00, pp. 95-96
Issue Date:: 2020-08-01

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Field	Value	Language
dc.contributor.author	Kovaleva, M
dc.contributor.author	Bulger, D
dc.contributor.author	Esselle, KP
dc.contributor.editor	Wang, CF
dc.contributor.editor	Shen, Z
dc.contributor.editor	Liu, EX
dc.contributor.editor	Tan, EL
dc.date	2020-08-24
dc.date.accessioned	2021-05-05T06:00:45Z
dc.date.available	2021-05-05T06:00:45Z
dc.date.issued	2020-08-01
dc.identifier.citation	Proceedings of the 2020 IEEE International Conference on Computational Electromagnetics, ICCEM 2020, 2020, 00, pp. 95-96
dc.identifier.isbn	9781728168234
dc.identifier.uri	http://hdl.handle.net/10453/148705
dc.description.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.
dc.language	en
dc.publisher	IEEE
dc.relation.ispartof	Proceedings of the 2020 IEEE International Conference on Computational Electromagnetics, ICCEM 2020
dc.relation.ispartof	2020 IEEE International Conference on Computational Electromagnetics
dc.relation.isbasedon	10.1109/ICCEM47450.2020.9219432
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Towards Demand-Driven Optimization Algorithms in Electromagnetic Engineering (Invited Paper)
dc.type	Conference Proceeding
utslib.citation.volume	00
utslib.location.activity	Singapore
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2021-05-05T06:00:44Z
pubs.finish-date	2020-08-26
pubs.publication-status	Published
pubs.start-date	2020-08-24
pubs.volume	00

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.

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http://hdl.handle.net/10453/148705