In recent years there has been an increasing attention to novel evolutionary optimization techniques employed to engineering and real-world applications. Among these, the design of antennas and electromagnetic devices is a well-established field of application. Black-hole PSO (bhPSO) is a novel version of PSO, which is here considered for antennas optimization. It is based on the concept of repulsion among particles when they get stuck in local optima. Stud Genetic Algorithm (SGA) is a rather old but quite unknown version of Genetic Algorithm, which is here considered for antennas optimization and compared to the recently developed algorithm called Social Network Optimization (SNO), based on the social network metaphor. The design of a planar reflectarray is here addressed in order to compare their performances on EM optimization problems. Reported results show their effectiveness in dealing with antenna optimization.

Novel population-based algorithms for reflectarray optimization

ZICH, RICCARDO;NICCOLAI, ALESSANDRO;GRIMACCIA, FRANCESCO;MUSSETTA, MARCO
2014-01-01

Abstract

In recent years there has been an increasing attention to novel evolutionary optimization techniques employed to engineering and real-world applications. Among these, the design of antennas and electromagnetic devices is a well-established field of application. Black-hole PSO (bhPSO) is a novel version of PSO, which is here considered for antennas optimization. It is based on the concept of repulsion among particles when they get stuck in local optima. Stud Genetic Algorithm (SGA) is a rather old but quite unknown version of Genetic Algorithm, which is here considered for antennas optimization and compared to the recently developed algorithm called Social Network Optimization (SNO), based on the social network metaphor. The design of a planar reflectarray is here addressed in order to compare their performances on EM optimization problems. Reported results show their effectiveness in dealing with antenna optimization.
Proceedings - 2014 International Conference on Electromagnetics in Advanced Applications, ICEAA 2014
9781467357104
978-1-4799-7325-5
Electrical and Electronic Engineering; Radiation
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/969454
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