Global optimization methods to design vacuum electronic devices

Abstract

In this paper, we try to adopt the global optimization method to design vacuum electronic devices. Based on the platform of three dimensional particle-in-cell (PIC) CHIPIC, the modules of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) are designed to optimize vacuum electronic devices, respectively. The comparisons of PSO and GA are implemented to optimize the slow wave period structure (SWS) of a relativistic backward wave oscillator (RBWO). The results show that the performances (optimization result and convergence speed) of PSO are better than that of GA in the cases of a small population size.