Simulation Optimization through Regression or Kriging Metamodels

This chapter surveys two methods for the optimization of real-world systems that are modelled through simulation. These methods use either linear regression metamodels, or Kriging (Gaussian processes). The metamodel type guides the design of the experiment; this design …fixes the input combinations of the simulation model. These regression models uses a sequence of local fi…rst-order and second-order polynomials— known as response surface methodology (RSM). Kriging models are global, but are re-estimated through sequential designs. "Robust" optimization may use RSM or Kriging, and accounts for uncertainty in simulation inputs