Pith. sign in

REVIEW

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2205.05759 v1 pith:JOGO2BG5 submitted 2022-05-11 cs.NE eess.SPphysics.app-ph

Efficient Antenna Optimization Using a Hybrid of Evolutionary Programing and Particle Swarm Optimization

classification cs.NE eess.SPphysics.app-ph
keywords hybridantennaoptimizationevolutionaryswarmtechniquealgorithmefficient
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
0 comments
read the original abstract

In this paper, we present a hybrid of Evolutionary Programming (EP) and Particle Swarm Optimization (PSO) algorithms for numerically efficient global optimization of antenna arrays and metasurfaces. The hybrid EP-PSO algorithm uses an evolutionary optimization approach that incorporates swarm directions in the standard self-adaptive EP algorithm. As examples, we have applied this hybrid technique to two antenna problems: the side-lobe-level reduction of a non-uniform spaced (aperiodic) linear array and the beam shaping of a printed antenna loaded with a partially reflective metasurface. Detailed comparisons between the proposed hybrid EP-PSO technique and EP-only and PSO-only techniques are given, demonstrating the efficiency of this hybrid technique in the complex antenna design problems.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.