DocumentCode
2913283
Title
Local search for Ant colony system to improve the efficiency of small meander line RFID antennas
Author
Weis, Gerhard ; Lewis, Andrew ; Randall, Marcus ; Galehdar, Amir ; Thiel, David
Author_Institution
Inst. for Integrated & Intell. Syst., Griffith Univ., Brisbane, QLD
fYear
2008
fDate
1-6 June 2008
Firstpage
1708
Lastpage
1713
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 line 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.
Keywords
antennas; combinatorial mathematics; optimisation; radiofrequency identification; search problems; ant colony system; antenna design; antenna structure; backbite operator; combinatorial search; local search; manual tuning; meander line RFID antenna; path construction problem; Ant colony optimization; Antenna accessories; Antennas and propagation; Design engineering; Design optimization; Dipole antennas; Manufacturing; RFID tags; Radio frequency; Radiofrequency identification; RFID antenna design; ant colony system optimisation; backbite operator;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
Conference_Location
Hong Kong
Print_ISBN
978-1-4244-1822-0
Electronic_ISBN
978-1-4244-1823-7
Type
conf
DOI
10.1109/CEC.2008.4631020
Filename
4631020
Link To Document