TY - CHAP
T1 - Using ant colony optimisation to construct meander-line RFID antennas
AU - Lewis, Andrew
AU - Randall, Marcus
AU - Galehdar, Amir
AU - Thiel, David V.
AU - Weis, Gerhard
PY - 2009
Y1 - 2009
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=78049279793&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-01262-4_8
DO - 10.1007/978-3-642-01262-4_8
M3 - Chapter
AN - SCOPUS:78049279793
SN - 9783642012617
VL - 210
T3 - Studies in Computational Intelligence
SP - 189
EP - 217
BT - Biologically-Inspired Optimisation Methods: Parallel Algorithms, Systems and Applications
ER -