simulation, EGO uses ordinary Kriging (OK), which is a special case of universal Kriging (UK). In our EGO variant we use …, EGO uses stochastic Kriging (SK), but we use stochastic IK (SIK). Moreover, in random simulation, EGO needs to select the … simulated system. EGO treats the simulation model as a black-box, and balances local and global searches. In deterministic …

answer the following questions: (i) How realistic are these classic assumptions in simulation practice? (ii) How can these … assumptions be tested? (iii) If assumptions are violated, can the simulation's I/O data be transformed such that the assumptions …

models with multiple random responses.Such models arise in simulation-based optimization with multivariate outputs. This … the simulation outputs are feasible, and whether any constraints are binding. The paper applies the new procedure to both … a synthetic example and an inventory simulation; the empirical results are encouraging …

Many simulation practitioners can get more from their analyses by using the statistical theory on design of experiments …. Furthermore, we provide a research agenda listing problems in the design of simulation experiments - as opposed to real world … of a particular simulation model or system; (2) finding robust decisions or policies; and (3) comparing the merits of …