Embedded stochastic-deterministic optimization method with accuracy control

A distributed evolutionary strategy is used to solve the optimization problem in a subspace of the searching space. At each cost function evaluation, a deterministic method is used to find the optimal solution in the complementary subspace, with an imposed accuracy. The proposed method is applied to solve TEAM Workshop problem 22 with the control of the numerical error. In this case the stochastic method acts in the geometrical parameter subspace and an embedded deterministic technique is used in the 2D current densities subspace. The application of the technique to superconducting magnetic energy storage is discussed.