Multi-Objective Optimization of Wire Antennas: Genetic Algorithms Versus Particle Swarm Optimization
The paper is aimed to the multi-objective optimization of wire multi-band antennas. Antennas are numerically modeled using time-domain integral-equation method. That way, the designed antennas can be characterized in a wide band of frequencies within a single run of the analysis. Antennas are optimized to reach the prescribed matching, to exhibit the omni-directional constant gain and to have the satisfactory polarization purity. Results of the design are experimentally verified. The multi-objective cost function is minimized by the genetic algorithm and by the particle swarm optimization. Results of the optimization by both the multi-objective methods are in detail compared. The combination of the time domain analysis and global optimization methods for the broadband antenna design and the detailed comparison of the multi-objective particle swarm optimization with the multi-objective genetic algorithm are the original contributions of the paper.
KeywordsWire antennas, multi-band antennas, multi-objective optimization, time-domain integral-equation method, genetic algorithms, particle swarm optimization
Document typePeer reviewed
Document versionFinal PDF
SourceRadioengineering. 2005, vol. 14, č. 4, s. 91-97. ISSN 1210-2512
- 2005/4