The idea of using a simpler surrogate to represent a complex phenomenon has gained
increasing popularity over past three decades. Due to their ability to exploit the black-box …

Responses of many real-world problems can only be evaluated perturbed by noise. In order
to make an efficient optimization of these problems possible, intelligent optimization …

Abstract Digital Soil Map** is becoming increasingly operational because of shared
approaches, clear specifications (eg, GlobalSoilMap) and more “practical” applications …

This article surveys the most relevant kriging-based infill algorithms for multiobjective
simulation optimization. These algorithms perform a sequential search of so-called infill …

In this article we investigate the unconstrained optimization (minimization) of the
performance of a system that is modeled through a discrete-event simulation. In recent …

Résumé This work is on Gaussian-process based approximation of a code which can be run
at different levels of accuracy. The goal is to improve the predictions of a surrogate model of …

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

Simulation-based optimization is a research area that is currently attracting a lot of attention
in many industrial applications, where expensive simulators are used to approximate …

Thermoplastic polymers used in aeronautical structures such as poly-ether-ether-ketone
(PEEK) usually exhibit nonlinear stress-strain relationships, which can be usually predicted …

Metamodels are commonly used as fast surrogates for the objective function to facilitate the
optimization of simulation models. Kriging (or the Gaussian process model) is a very popular …