Local search for ant colony system to improve the efficiency of small meander line RFID antennas

Gerhard Weis, Andrew Lewis, Marcus Randall, Amir Galehdar, David V. Thiel

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

15 Citations (Scopus)

Abstract

The efficient design of meander line antennas for RFID devices is a significant real-world problem. Traditional manual tuning of antenna designs is becoming impractical for larger problems. Thus the use of automated techniques, in the form of combinatorial search algorithms, is a necessity. Ant colony system (ACS) is a very efficient meta-heuristic that is commonly used to solve path construction problems. Apart from its own native search capacity, ACS can be dramatically improved by combining it with local search strategies. As shown in this paper, applying local search as a form of structure refinement to RFID meander tine antennas delivers effective antenna structures. In particular, we use the operator known as backbite, that has had previous application in the construction of self-avoiding walks and compact polymer chains. Moreover, we apply it in a novel, hierarchical manner that allows for good sampling of the local search space. Its use represents a significant improvement on results obtained previously.

Original languageEnglish
Title of host publicationIEEE Congress on Evolutionary Computation 2008
Subtitle of host publicationCEC 2008
PublisherIEEE Canada
Pages1708-+
Number of pages2
ISBN (Print)978-1-4244-1822-0
DOIs
Publication statusPublished - 2008
EventIEEE Congress on Evolutionary Computation - Hong Kong, China
Duration: 1 Jun 20086 Jun 2008

Publication series

NameIEEE Congress on Evolutionary Computation
PublisherIEEE

Conference

ConferenceIEEE Congress on Evolutionary Computation
Abbreviated titleCEC 2008
CountryChina
CityHong Kong
Period1/06/086/06/08

Cite this

Weis, G., Lewis, A., Randall, M., Galehdar, A., & Thiel, D. V. (2008). Local search for ant colony system to improve the efficiency of small meander line RFID antennas. In IEEE Congress on Evolutionary Computation 2008: CEC 2008 (pp. 1708-+). (IEEE Congress on Evolutionary Computation). IEEE Canada. https://doi.org/10.1109/CEC.2008.4631020
Weis, Gerhard ; Lewis, Andrew ; Randall, Marcus ; Galehdar, Amir ; Thiel, David V. / Local search for ant colony system to improve the efficiency of small meander line RFID antennas. IEEE Congress on Evolutionary Computation 2008: CEC 2008. IEEE Canada, 2008. pp. 1708-+ (IEEE Congress on Evolutionary Computation).
@inproceedings{df12ff0f7bf74e83a1c3c8e2d98d3f22,
title = "Local search for ant colony system to improve the efficiency of small meander line RFID antennas",
abstract = "The efficient design of meander line antennas for RFID devices is a significant real-world problem. Traditional manual tuning of antenna designs is becoming impractical for larger problems. Thus the use of automated techniques, in the form of combinatorial search algorithms, is a necessity. Ant colony system (ACS) is a very efficient meta-heuristic that is commonly used to solve path construction problems. Apart from its own native search capacity, ACS can be dramatically improved by combining it with local search strategies. As shown in this paper, applying local search as a form of structure refinement to RFID meander tine antennas delivers effective antenna structures. In particular, we use the operator known as backbite, that has had previous application in the construction of self-avoiding walks and compact polymer chains. Moreover, we apply it in a novel, hierarchical manner that allows for good sampling of the local search space. Its use represents a significant improvement on results obtained previously.",
author = "Gerhard Weis and Andrew Lewis and Marcus Randall and Amir Galehdar and Thiel, {David V.}",
year = "2008",
doi = "10.1109/CEC.2008.4631020",
language = "English",
isbn = "978-1-4244-1822-0",
series = "IEEE Congress on Evolutionary Computation",
publisher = "IEEE Canada",
pages = "1708--+",
booktitle = "IEEE Congress on Evolutionary Computation 2008",
address = "Canada",

}

Weis, G, Lewis, A, Randall, M, Galehdar, A & Thiel, DV 2008, Local search for ant colony system to improve the efficiency of small meander line RFID antennas. in IEEE Congress on Evolutionary Computation 2008: CEC 2008. IEEE Congress on Evolutionary Computation, IEEE Canada, pp. 1708-+, IEEE Congress on Evolutionary Computation, Hong Kong, China, 1/06/08. https://doi.org/10.1109/CEC.2008.4631020

Local search for ant colony system to improve the efficiency of small meander line RFID antennas. / Weis, Gerhard; Lewis, Andrew; Randall, Marcus; Galehdar, Amir; Thiel, David V.

IEEE Congress on Evolutionary Computation 2008: CEC 2008. IEEE Canada, 2008. p. 1708-+ (IEEE Congress on Evolutionary Computation).

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

TY - GEN

T1 - Local search for ant colony system to improve the efficiency of small meander line RFID antennas

AU - Weis, Gerhard

AU - Lewis, Andrew

AU - Randall, Marcus

AU - Galehdar, Amir

AU - Thiel, David V.

PY - 2008

Y1 - 2008

N2 - The efficient design of meander line antennas for RFID devices is a significant real-world problem. Traditional manual tuning of antenna designs is becoming impractical for larger problems. Thus the use of automated techniques, in the form of combinatorial search algorithms, is a necessity. Ant colony system (ACS) is a very efficient meta-heuristic that is commonly used to solve path construction problems. Apart from its own native search capacity, ACS can be dramatically improved by combining it with local search strategies. As shown in this paper, applying local search as a form of structure refinement to RFID meander tine antennas delivers effective antenna structures. In particular, we use the operator known as backbite, that has had previous application in the construction of self-avoiding walks and compact polymer chains. Moreover, we apply it in a novel, hierarchical manner that allows for good sampling of the local search space. Its use represents a significant improvement on results obtained previously.

AB - The efficient design of meander line antennas for RFID devices is a significant real-world problem. Traditional manual tuning of antenna designs is becoming impractical for larger problems. Thus the use of automated techniques, in the form of combinatorial search algorithms, is a necessity. Ant colony system (ACS) is a very efficient meta-heuristic that is commonly used to solve path construction problems. Apart from its own native search capacity, ACS can be dramatically improved by combining it with local search strategies. As shown in this paper, applying local search as a form of structure refinement to RFID meander tine antennas delivers effective antenna structures. In particular, we use the operator known as backbite, that has had previous application in the construction of self-avoiding walks and compact polymer chains. Moreover, we apply it in a novel, hierarchical manner that allows for good sampling of the local search space. Its use represents a significant improvement on results obtained previously.

U2 - 10.1109/CEC.2008.4631020

DO - 10.1109/CEC.2008.4631020

M3 - Conference contribution

SN - 978-1-4244-1822-0

T3 - IEEE Congress on Evolutionary Computation

SP - 1708-+

BT - IEEE Congress on Evolutionary Computation 2008

PB - IEEE Canada

ER -

Weis G, Lewis A, Randall M, Galehdar A, Thiel DV. Local search for ant colony system to improve the efficiency of small meander line RFID antennas. In IEEE Congress on Evolutionary Computation 2008: CEC 2008. IEEE Canada. 2008. p. 1708-+. (IEEE Congress on Evolutionary Computation). https://doi.org/10.1109/CEC.2008.4631020