Fast Design of Waveguide Microwave Filters Using Genetic Algorithm and Particle Swarm Optimization Based on the S-parameters Method

In this article an accurate and efficient procedure to design microwave waveguide filters is presented which is based on the S-parameters method combined with optimization algorithms. The proposed method is fast, since only the full-wave characteristics of a small part of the filter (one building block) are required to design the whole filter. Three different optimization algorithms; genetic algorithm (GA), particle swarm optimization algorithm (PSO) and quantum particle swarm optimization algorithm (QPSO) are used for tuning the filter response and their performances in filter design are compared. This approach is verified through full-wave simulation using commercial software for post filter, iris filter, and E-plane metal insert filter at Ku, X and W frequency bands, respectively.