Abstract: Factor screening searches for the really important inputs (factors) among the many inputs that are changed in a realistic simulation experiment. Sequential bifurcation (SB) is a sequential method that changes groups of inputs simultaneously. SB is the most efficient and effective...

Textbooks on Design Of Experiments invariably start by explaining why one-factor-at-a -time (OAT) is an inferior method. Here we will show that in a model with all interactions a variant of OAT is extremely efficient, provided that we only have non-negative parameters and that there are only a...

This paper derives a novel procedure for testing the Karush-Kuhn-Tucker (KKT) first-order optimality conditions in models with multiple random responses.Such models arise in simulation-based optimization with multivariate outputs.This paper focuses on expensive simulations, which have small...

Abstract: Factor screening searches for the really important inputs (factors) among the many inputs that are changed in a realistic simulation experiment. Sequential bifurcation (or SB) is a sequential method that changes groups of inputs simultaneously. SB is the most e¢ cient and effective...

This paper studies simulation-based optimization with multiple outputs. It assumes that the simulation model has one random objective function and must satisfy given constraints on the other random outputs. It presents a statistical procedure for test- ing whether a specific input combination...