Using ant colony optimisation to construct meander-line RFID antennas

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

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterResearchpeer-review

15 Citations (Scopus)

Abstract

A method increasingly used to uniquely identify objects (be they pieces of luggage, transported goods or inventory items in shops and warehouses), is Radio Frequency IDentification (RFID). One of the most important components of RFID systems is the antenna and its design is critical to the utility of such tracking systems. Design engineers have traditionally constructed small antennas using their knowledge and intuition, as there is no simple analytical solution relating antenna structure to performance. This, however, does not guarantee optimal results, particularly for larger, more complex antennas. The problem is ideally suited to automated methods of optimisation. This chapter presents an overview of the automatic design of antennas using the meta-heuristic known as Ant Colony Optimisation (ACO). Apart from a description of the necessary mechanics ACO needs to effectively solve this problem, a novel local search refinement operator and a multi-objective version of the problem are also described. The latter is used to optimise both antenna efficiency and resonant frequency. Computational results for a range of antenna sizes show that ACO is a very effective design tool for RFID antennas.

Original languageEnglish
Title of host publicationBiologically-Inspired Optimisation Methods: Parallel Algorithms, Systems and Applications
Pages189-217
Number of pages29
Volume210
DOIs
Publication statusPublished - 2009

Publication series

NameStudies in Computational Intelligence
Volume210
ISSN (Print)1860949X

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Lewis, A., Randall, M., Galehdar, A., Thiel, D. V., & Weis, G. (2009). Using ant colony optimisation to construct meander-line RFID antennas. In Biologically-Inspired Optimisation Methods: Parallel Algorithms, Systems and Applications (Vol. 210, pp. 189-217). (Studies in Computational Intelligence; Vol. 210). https://doi.org/10.1007/978-3-642-01262-4_8