Application of Gbest-guided artificial bee colony algorithm to passive UHF RFID tag design

Abstract

In this paper, new planar spiral antennas with meander lines and loads for passive Radiofrequency identification tag application at ultra-high-frequency band are designed and optimized using the global best (gbest)-guided Artificial Bee Colony (GABC) algorithm. The GABC is an improved Artificial Bee Colony algorithm, which includes gbest solution information into the search equation to improve the exploitation. The optimization goals are antenna size minimization, gain maximization, and conjugate matching. The antenna dimensions were optimized and evaluated in conjunction with commercial software FEKO. GABC is compared with other popular algorithms. The optimization results produced show that GABC is a powerful optimization algorithm that can be efficiently applied to tag antenna design problems.

Passive UHF RFID Tags with Specific Printed Antennas for Dielectric and Metallic Objects Applications

“…One of them is the easy theoretical calculation which can be preceded for the calculation of the input impedance, the radiated field and the gain, applying a hybrid combination of the Transmission Line Model and the low value of electromotive force induced to the spiral along with the Green function method [21]. The other advantage is that the branches of the spiral can be modified as meandered strip lines [23], or meandered and simultaneously loaded with small patches at the end or along branches [24], [25]. Although these additional modifications increase the number of geometrical parameters making, at a first glance, the antenna design more complicated, actually, in the published works it was proved that it turns to an advantage because offers more degrees of freedom which can be handled via optimization algorithms.…”

“…Although these additional modifications increase the number of geometrical parameters making, at a first glance, the antenna design more complicated, actually, in the published works it was proved that it turns to an advantage because offers more degrees of freedom which can be handled via optimization algorithms. In this way, effective tags can be designed [21][22][23][24][25].…”

“…Coupled shorted patches textured by comb-notches for efficient matching to the IC and utilization as an on-body sensors have been also proposed in [20]. Articles [21][22][23][24][25] suggest antennas of spiral shape which are properly modified via optimization techniques, for the required specifications of matching and gain levels to be obtained.…”

Evolutionary Algorithms Applied to Antennas and Propagation: A Review of State of the Art

“…A search in the Scopus database shows that there are more than 3000 papers on ABC, of which 48 use the ABC for antenna design. These include array design [93][94][95][96]; resonant frequency of patch antennas calculation [97]; and RFID tags design [98][99][100]. Ant Colony Optimization (ACO) [6,10,11] is a population-based metaheuristic which was introduced by Dorigo et al [11] inspired by the behavior of real ants.…”

Investigation on the Inversion of the Atmospheric Duct Using the Artificial Bee Colony Algorithm Based on Opposition-Based Learning

“…In ABC, the optimization procedures are implemented by simulating the intelligent foraging behavior of a honeybee swarm to share information of bees for the purpose of finding the optimal solution. Currently, the ABC algorithm has been applied to the design of antenna and electromagnetic devices [13][14][15]. In addition, the ABC algorithm has been used to infer the atmospheric duct from RFC technique [11], and the comparative study results demonstrate that the performance of ABC is superior to that of the PSO for the inversion of atmospheric duct.…”