Iterative Kriging-Based Methods for Expensive Black-Box Models

Reliability-based design optimization (RBDO) in electromagnetic field problems requires the calculation of probability of failure, leading to a huge computational cost in the case of expensive models. Three different RBDO approaches using a kriging surrogate model are proposed to overcome this difficulty by introducing an approximation of the objective function and constraints. These methods use different infill sampling criteria to add samples in the process of optimization or/and in the reliability analysis. Several enrichment criteria and strategies are compared in terms of the number of evaluations and accuracy of the solution.