This article reviews Kriging (also called spatial correlation modeling). It presents the basic
Kriging assumptions and formulas—contrasting Kriging and classic linear regression …

Simulation optimization is increasingly popular for solving complicated and mathematically
intractable business problems. Focusing on academic articles published between 1998 and …

This contribution summarizes the design and analysis of experiments with computerized
simulation models. It focuses on two metamodel (surrogate, emulator) types, namely first …

We extend the basic theory of kriging, as applied to the design and analysis of deterministic
computer experiments, to the stochastic simulation setting. Our goal is to provide flexible …

Simulation is a widely applied tool to study and evaluate complex systems. Due to the
stochastic and complex nature of real world systems, simulation models for these systems …

IN GENERAL, three sorts of aerodynamic testing are performed to develop products in the
aeronautical or automobile engineering field: full-scale track testing orflight testing, wind …

This article presents a novel heuristic for constrained optimization of computationally
expensive random simulation models. One output is selected as objective to be minimized …

Genetic programming (GP) and artificial neural networks (ANNs) can be used in the
development of surrogate models of complex systems. The purpose of this paper is to …

Many iterative optimization methods are designed to be used in conjunction with
deterministic objective functions. These optimization methods can be difficult to apply to an …

Inventory control has been a major point of discussion in industrial engineering and
operations research for over 100 years. Various advanced numerical methods can be used …