Discrete optimization problems of linear array synthesis by using real number particle swarm optimization

Abstract

It is generally believed genetic algorithm (GA) is superior to particle swarm optimization (PSO) while dealing with the discrete optimization problems. In this paper, a suitable mapping method is adopted and the modified PSO can effectively deal with the discrete optimization problems of linear array pattern synthesis. This strategy has been applied in thinned linear array pattern synthesis with minimum sidelobe level, 4-bit digital phase shifter linear array pattern synthesis and unequally spaced thinned array pattern synthesis with minimum sidelobe level. The obtained results are all superior to those in existing literatures with GA, iterative FFT and different versions of binary PSO, that show the effectiveness of this strategy and its potential application to other discrete electromagnetic optimization problems.