On Formulating and Designing Antenna Arrays by Evolutionary Algorithms

The design of antenna arrays is usually imposed with lots of requirements. The design can be modeled as different kinds of optimization problems, such as single-objective optimization problems (SOPs) with or without constraints or multiobjective optimization problems with or without constraints. Then, different optimizers need to be applied to deal with the corresponding optimization problems. There are two issues to be addressed for antenna designers: one is which kind of optimization problems is the fittest to model antenna arrays; the other is a general and efficient algorithm that can solve different kinds of problems. To this end, for the first issue, constrained multiobjective optimization problems (CMOPs) are recommended as the most suitable kind in this article because CMOPs not only fully reflect the requirements of array design but also cover SOPs, constrained optimization problems (COPs), and multiobjective optimization problems (MOPs) as degeneration cases. For the second issue, a dynamic constrained multiobjective evolutionary algorithm (DCMOEA) is provided to solve CMOPs. Notably, DCMOEA is a general framework that can also work well on SOPs, COPs, and MOPs. Finally, two examples of antenna arrays are designed to verify the proposed conclusion.