Comparison of different optimization techniques in microstrip filter design

Recently there is an increasing attention on some novel techniques among Evolutionary Optimization algorithms, such as Ant Colony Optimization (ACO), Biogeography Based Optimization (BBO), Differential Evolution (DE), Population-Based Incremental Learning (PBIL) and Stud Genetic Algorithm (SGA). The design of a microwave microstrip pass-band filter is here addressed considering different recently developed evolutionary optimization algorithms, in order to compare their performances on a benchmark EM optimization problem. Results show that some techniques (DE, BBO, SGA) are particularly effective in dealing with this kind of complex EM problem.