Analysis and Parametric Optimization of a Turn of a Meander Microstrip Line in Various Environments

The paper presents the results of the analysis and parametric optimization of a meander microstrip line in various climatic conditions. The optimization was performed by the two methods: genetic algorithms (GA) and evolutionary strategies (ES), and using one and two criteria. Various environmental conditions were represented by ice, water, and air. The analysis showed that changing from the air-filled layer to the water layer increased the per-unit-length delays of the odd and even modes by 55% and 18%. Whereas introducing the ice layer increased the delays by 511% and 173%, respectively. The optimization results of the two methods showed good agreement. However, with the similar sets of optimal parameters obtained, the optimization using ES was up to 3.3 times faster than the optimization using GA.