In recent years there has been an increasing attention to novel evolutionary optimization techniques. A recently developed algorithm called Social Network Optimization (SNO), based on the emulation of decision making process in social network environments, is here considered and compared to Stud Genetic Algorithm (SGA). The design of a planar array is here addressed in order to compare their performances on a benchmark EM optimization problem. Reported results show their effectiveness in dealing with antenna optimization.

Planar array optimization by means of SNO and StudGA

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

Abstract

In recent years there has been an increasing attention to novel evolutionary optimization techniques. A recently developed algorithm called Social Network Optimization (SNO), based on the emulation of decision making process in social network environments, is here considered and compared to Stud Genetic Algorithm (SGA). The design of a planar array is here addressed in order to compare their performances on a benchmark EM optimization problem. Reported results show their effectiveness in dealing with antenna optimization.
2014
2014 IEEE Antennas and Propagation Society International Symposium (APSURSI)
9781479935376
9781479935383
9781479935406
Algorithms; Decision making; Genetic algorithms; Optimization; Social networking (online); Antenna optimization; Decision making process; EM optimizations; Evolutionary Optimization Techniques; Network environments; Network optimization; Planar arrays
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/861547
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