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Integrating continuous differential evolution with discrete local search for meander line RFID antenna design
Citation
Montgomery, J and Randall, M and Lewis, A, Integrating continuous differential evolution with discrete local search for meander line RFID antenna design, PLoS ONE, 14, (10) Article e0223194. ISSN 1932-6203 (2019) [Refereed Article]
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Copyright Statement
Copyright 2019 Montgomery et al. Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/
DOI: doi:10.1371/journal.pone.0223194
Abstract
The automated design of meander line RFID antennas is a discrete self-avoiding walk (SAW) problem for which efficiency is to be maximized while resonant frequency is to be minimized. This work presents a novel exploration of how discrete local search may be incorporated into a continuous solver such as differential evolution (DE). A prior DE algorithm for this problem that incorporates an adaptive solution encoding and a bias favoring antennas with low resonant frequency is extended by the addition of the backbite local search operator and a variety of schemes for reintroducing modified designs into the DE population. The algorithm is extremely competitive with an existing ACO approach and the technique is transferable to other SAW problems and other continuous solvers. The findings indicate that careful reintegration of discrete local search results into the continuous population is necessary for effective performance.
Item Details
Item Type: | Refereed Article |
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Keywords: | evolutionary computation, RFID, RFID antenna, multiobjective optimisation, local search, differential evolution |
Research Division: | Information and Computing Sciences |
Research Group: | Machine learning |
Research Field: | Neural networks |
Objective Division: | Expanding Knowledge |
Objective Group: | Expanding knowledge |
Objective Field: | Expanding knowledge in the information and computing sciences |
UTAS Author: | Montgomery, J (Dr James Montgomery) |
ID Code: | 135704 |
Year Published: | 2019 |
Deposited By: | Information and Communication Technology |
Deposited On: | 2019-11-08 |
Last Modified: | 2020-05-18 |
Downloads: | 27 View Download Statistics |
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