Robust Optimization in Simulation: Taguchi and Krige Combined

Simulation-optimization aims to identify the setting of the input parameters (input variables, factors) of the simulated system that leads to the optimal system performance. In practice, however, some of these parameters cannot be perfectly controlled — due to measurement errors or other implementation issues, and the inherent uncertainty caused by fluctuations in the environment (e.g., demand). Consequently, the classic optimal solution may turn out to be either sub-optimal or infeasible.