This chapter presents design cases from different microwave structure cases. The problem of a planar microwave absorber design lies in the minimization of the reflection coefficient of an incident plane wave in a multilayer structure for a desired range of angles and frequencies. The reflection coefficient depends on the thickness and the electric and magnetic properties of each layer. Several studies, which address this problem, exist in the literature. Evolutionary algorithms (EAs) like genetic algorithms (GAs) have been in several occasions applied in absorber design. In, a microGA algorithm with a predefined materials database was applied. The major drawback of a GA approach is the difficulty in implementation due to the algorithm-inherited complexity and the required long computational time. Moreover, the application of swarm intelligence optimizers in electromagnetic (EM) design problems has attracted several researchers. Particle swarm optimization (PSO) has also been used successfully in absorber design problems. Recently, artificial bee colony (ABC)has been applied in several cases to microwave absorber design. Differential evolution (DE) has also been applied to absorber design problem. A comparative study between PSO and DE for the microwave absorber design problems is reported. Moreover, other emerging nature-inspired algorithms have been deployed in the literature for solving the abovementioned problem.

Chapter Contents:

• 5.1 Design of microwave broadband absorbers
• 5.1.1 Problem formulation
• 5.1.2 Single-objective absorber optimization
• 5.1.2.1 Statistical analysis of results
• 5.1.3 Multi-objective absorber optimization
• 5.2 Dielectric filters design
• 5.2.1 Problem formulation
• 5.2.2 Single-objective optimization of dielectric filters
• 5.2.2.1 Statistical analysis of results
• 5.2.3 Multi-objective optimization
• 5.3 Microstrip filters design
• 5.3.1 Microstrip band-pass filter
• 5.3.2 Single band open-loop ring resonator filter
• 5.3.3 Dual-band OLRR filter
• References

Inspec keywords: microwave materials; reflectivity; artificial bee colony algorithm; microwave absorption; particle swarm optimisation; design engineering; genetic algorithms; swarm intelligence

Other keywords: evolutionary algorithms; swarm intelligence optimisers; microwave structures; genetic algorithms; differential evolution; planar microwave absorber; design engineering; artificial bee colony; magnetic properties; electric properties; reflection coefficient; incident plane wave; particle swarm optimization

Subjects: Project and design engineering; Microwave materials and structures; Optimisation techniques