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Particle Swarm Optimization Algorithm in Electromagnetics- Case Studies: Reconfigurable Radiators and Cancer Detection
Abstract
This chapter is intended to describe the vast intrinsic potential of the swarm-intelligence-based algorithms in solving complicated electromagnetic problems. This task is accomplished through addressing the design and analysis challenges of some key real-world problems, ranging from the design of wearable radiators to tumor detection tools. Some of these problems have already been tackled by solution techniques other than particle swarm optimization (PSO) algorithm, the results of which can be found in the literature. However, due to the relatively high level of complexity and randomness inherent to these problems, one has to resort to oversimplification in order to arrive at reasonable solutions utilizing analytical techniques. In this chapter, the authors discuss some recent studies that utilize PSO algorithm particularly in two emerging areas; namely, efficient design of reconfigurable radiators and permittivity estimation of multilayer structures. These problems, although unique, represent a broader range of problems in practice which employ microwave techniques for antenna design and microwave imaging.
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