Optimization of a Vircator using a novel evolutionary algorithm designed to reducing the number of evaluations

This paper presents an optimization of a virtual cathode oscillator (Vircator) with axial extraction using a novel evolutionary algorithm (EA) thought to reduce the number of evaluations. The EA was tested on a Vircator optimization with two objective functions to maximize the radiated energy and to tune the resonance frequency at 5GHz. The simulations were made on CST Particle Studio. The EA was programed in Matlab. The proposed EA is an effort to reduce the computational time used to optimize problems where the objective function should be obtained using computational simulation. At the end, the algorithm identified a zone into the search space where the optimal solution can be found. Results are accord with a previous Vircator optimization using NSGA-II.