Abstract: Based on platform of three-dimensional particle-in-cell (PIC), CHIPIC, modules of particle swarm optimization (PSO) and genetic algorithm (GA) are designed to optimize a relativistic backward wave oscillator (RBWO), respectively. Comparisons of PSO and GA are implemented in three kinds of parameters of RBWO:Continuous parameter, discrete parameter, and mix parameters. It shows that performances of PSO are better than that of GA. PSO has higher optimization accuracy and convergence rate than GA.

Key words: particle swarm optimization, genetic algorithm, relativistic backward wave oscillator, particle-in-cell