Course Activities

This seminar aims to discuss the technical trends and challenges of global optimization techniques. Optimization can be thought as the art of making good decisions. Evolutionary algorithms (EAs) belong to the family of stochastic optimizers. Several evolutionary algorithms (EAs) have emerged in the past decades that mimic biological entities behavior and evolution. EAs are widely used for the solution of single and multi-objective optimization engineering problems. The EAs have also been applied to a variety of microwave component, antenna design, radar design, and wireless communications problems. These techniques, among others, include Genetic Algorithms (GAs), Evolution Strategies (ES), Particle Swarm Optimization (PSO), and Differential evolution (DE. In addition, new innovative algorithms that are not only biology-based but also physics-based or chemistry-based have emerged. The use of the above algorithms has an increasing impact on real-world engineering problems. School participants will gain fundamental theoretical and practical knowledge and a wide perspective on the above focus areas. Moreover, they will learn in practice by experimenting with MATLAB exercises.


  1. Theory,
  2. Exercises (MATLAB) including applications to EM,
  3. Student competition (benchmark function),
  4. Electronic form assessment/exam,
  5. Student appreciation/comments form