Multi-Objective Optimization of Wire Antennas: Genetic Algorithms Versus Particle Swarm Optimization

Abstract

The paper is aimed to the multi-objective optimization of wiremulti-band antennas. Antennas are numerically modeled using time-domainintegral-equation method. That way, the designed antennas can becharacterized in a wide band of frequencies within a single run of theanalysis. Antennas are optimized to reach the prescribed matching, toexhibit the omni-directional constant gain and to have the satisfactorypolarization purity. Results of the design are experimentally verified. The multi-objective cost function is minimized by the genetic algorithmand by the particle swarm optimization. Results of the optimization byboth the multi-objective methods are in detail compared. The combination of the time domain analysis and global optimizationmethods for the broadband antenna design and the detailed comparison ofthe multi-objective particle swarm optimization with themulti-objective genetic algorithm are the original contributions of thepaper.