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Abstract-In this paper, a new evolutionary learning algorithm based on a hybrid of improved real-code genetic algorithm (IGA) and particle swarm optimization (PSO) called HIGAPSO is proposed. In order to overcome the drawbacks of standard genetic algorithm and particle swarm optimization, some improved mechanisms based on non-linear ranking selection, competition and selection among several crossover offspring and adaptive change of mutation scaling are adopted in the genetic algorithm, and dynamical parameters are adopted in PSO. The new population is produced through three approaches to improve the global optimization performance, which are elitist strategy, PSO strategy and improved genetic algorithm (IGA) strategy. The effectiveness of the proposed algorithm has been compared with GAs and PSO, synthesizing a circular array, a linear array and a base station array. Results show that the proposed algorithm is able to adapt itself to different electromagnetic optimization problems more effectively.

Abstract-A method of designing a cylindrical conformal array with shaped-beam and reconfigurable dual-beam using a modified particle swarm optimization algorithm is proposed in this paper. The proposed algorithm is easy to implement and efficient to be used in synthesizing conformal arrays with digital attenuators and digital phase shifters. Moreover, the proposed synthesis has taken the actual active element patterns into account, which can reduce the error between computation and realization. Good agreement can be obtained between the desired patterns and the synthesized patterns.

In this article, an extended particle swarm optimization (EPSO) algorithm is proposed for designing conformal phased arrays. On the basis of traditional particle swarm optimization (PSO), novel velocity updating mechanism, new exceeding boundary control operator, and global best perturbation are introduced in EPSO to overcome the drawbacks of PSO. To validate the efficiency of the proposed algorithm, both the classical test functions and the scenarios concerning a 1 Â 9-element cylindrical conformal phased array and a 3 Â 9(27)-element cylindrical conformal array with flat-top shaped-beam pattern are presented. Simulation results show that the proposed method is superior to genetic algorithm (GA) and PSO when applied to both the classical test functions and the practical problems of conformal antenna array synthesis.