Local Search for Ant Colony System to Improve the Efficiency of Small Meander Line RFID Antennas

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Title Local Search for Ant Colony System to Improve the Efficiency of Small Meander Line RFID Antennas
Author Weis, Gerhard; Lewis, Andrew; Randall, Marcus; Mohammadzadeh Galehdar, Amir Abas; Thiel, David Victor
Publication Title IEEE Congress on Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence).
Editor Michalewicz and Reynolds
Year Published 2008
Place of publication Online
Publisher Online
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.
Peer Reviewed Yes
Published Yes
Publisher URI http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=4625778
Alternative URI http://dx.doi.org/10.1109/CEC.2008.4631020
Copyright Statement Copyright 2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
ISBN 978-1-4244-1822-0
Conference name 2008 IEEE World Congress on Computational Intelligence
Location Hong Kong, China
Date From 2008-06-01
Date To 2008-06-06
URI http://hdl.handle.net/10072/23663
Date Accessioned 2008-09-09
Language en_AU
Faculty Faculty of Science, Environment, Engineering and Technology
Subject PRE2009-Optimisation; PRE2009-Simulation and Modelling
Publication Type Conference Publications (Full Written Paper - Refereed)
Publication Type Code e1

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