. As a novel metamodel we introduce intrinsic Kriging, for either deterministic or random simulation. For deterministic … simulation we study the famous `efficient global optimization' (EGO) method, substituting intrinsic Kriging for universal Kriging …. For random simulation we investigate a state-of-the-art two-stage algorithm accounting for heteroscedastic variances of …

a realistic simulation experiment. Sequential bifurcation (SB) is a sequential method that changes groups of inputs …-order polynomials are adequate approximations of the input/output functions implied by the simulation model; (ii) the signs of all first … either (heredity property). This paper examines SB for random simulation with multiple responses (outputs), called …

simulation models. This contribution discusses the different types of DOE for these three domains, but focusses on random … simulation. DOE may have two goals: sensitivity analysis including factor screening and optimization. This contribution starts …

- ceptable. The methodology combines simulation, bootstrapping, and metamodeling. The methodology is illustrated through a …-factorial design. The resulting simulation In- put/Output (I/O) data are analyzed through a first-order polynomial metamodel and …

Abstract: To analyze the input/output behavior of simulation models with multiple responses, we may apply either …

This paper proposes a novel method to select an experimental design for interpolation in random simulation, especially … discrete event simulation.(Though the paper focuses on Kriging, this design approach may also apply to other types of … metamodels such as linear regression models.)Assuming that simulation requires much computer time, it is important to select a …