Optimization of Microstrip Structures with Modal Phenomena Using Metaheuristic Iterative Global Optimization Algorithms

This paper is the first to consider the optimization of a microstrip modal filter (MF) using three metaheuristic global optimization algorithms based on deterministic and probabilistic search. More specifically, we employ simplicial homology (SHGO), branch and bound (BnB), and simulated annealing (SA) algorithms. Our optimization results are compared with earlier ones obtained using evolutionary algorithms (simple genetic algorithm and evolutionary strategies) and random search method. In this study, the structure is optimized according to the criterion of minimizing the maximum voltage level at the output of the MF (amplitude criterion). As a result, a minimum MF output voltage for SHGO optimization is 146.2 mV, for BnB - 146.3 mV, and for SA-147.6 mV. Thus, we demonstrate the feasibility of using algorithms based on deterministic and probabilistic search, and determine the features and limitations of each algorithm, as well as their advantages and disadvantages. In addition, some recommendations are given in terms of how to choose an algorithm for the most effective optimization of strip MFs.