Automated optimal design techniques for inverse electromagnetic problems

The solution of Inverse Electromagnetic problems requires to minimize or maximize a Cost Function, related to field quantities. The choice of the best algorithm to be used depends on several factors, e.g. the Cost Function complexity and the number of Design Variables. The paper presents two methods based on different approaches. The first, based on a deterministic approach, considers a quadratic approximation of the Cost Function, whose minimum is faster to calculate. The second, based on a stochastic approach, is derived from the Simulated Annealing algorithm. Both methods, implemented as computer codes, have been applied for the solution of a test synthesis problem where the magnetic field is generated by discrete coils. The results are compared and discussed.