Managers wish to verify that a particular engineering design meets their require- ments. This design's future environment will differ from the environment assumed during the design. Therefore it is crucial to determine which variations in the envi- ronment may make this design unacceptable. The...

Abstract: To analyze the input/output behavior of simulation models with multiple responses, we may apply either univariate or multivariate Kriging (Gaussian process) metamodels. In multivariate Kriging we face a major problem: the covariance matrix of all responses should remain positive-de...

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...

Optimization of simulated systems is the goal of many methods, but most methods as- sume known environments. We, however, develop a `robust' methodology that accounts for uncertain environments. Our methodology uses Taguchi's view of the uncertain world, but replaces his statistical techniques...

Abstract: This paper investigates two related questions: (1) How to derive a confidence interval for the output of a combination of simulation inputs not yet simulated? (2) How to select the next combination to be simulated when searching for the optimal combination? To answer these questions,...

This article uses a sequentialized experimental design to select simulation input com- binations for global optimization, based on Kriging (also called Gaussian process or spatial correlation modeling); this Kriging is used to analyze the input/output data of the simulation model (computer...

This paper proposes a unified framework for measuring and managing longevity risk. Specifically, we develop a flexible framework for valuing survivor derivatives like forwards, swaps, as well as options both of European and American style. Our framework is essentially independent of the assumed...

In this paper we investigate global optimization for black-box simulations using metamodels to guide this optimization. As a novel metamodel we introduce intrinsic Kriging, for either deterministic or random simulation. For deterministic simulation we study the famous `efficient global...

This article describes an expert system, COT-XPERT, developed for controlling pests and diseases affecting cotton crop as well as a system for Rice Stem Borers (RSB) simulation. The system works in two parts: The first part addresses the issues of efficient use of knowledge for RSB problem and...

Monte Carlo Methoden haben sich auf vielen Gebieten der Statistik und Ökonometrie als wertvolles Instrument erwiesen. Die übliche Verwendung von Pseudozufallszahlen führt dazu, daß der Zusammenhang zwischen einem allgemeinen Zufallsbegriff und der Anwendung in Monte Carlo Verfahren eher ein...