Kriging is a popular method for estimating the global optimum of a simulated system. Kriging approximates the input/output function of the simulation model. Kriging also estimates the variances of the predictions of outputs for input combinations not yet simulated. These predictions and their...

Classic linear regression models and their concomitant statistical designs assume a univariate response and white noise.By definition, white noise is normally, independently, and identically distributed with zero mean.This survey tries to answer the following questions: (i) How realistic are...

Generalized Response Surface Methodology (GRSM) is a novel general-purpose metaheuristic based on Box and Wilson.s Response Surface Methodology (RSM).Both GRSM and RSM estimate local gradients to search for the optimal solution.These gradients use local first-order polynomials.GRSM, however,...

AMS classifications: 62G08, 62G10, 62G20, 62G30; 60F17.

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...

Whereas Operations Research has always paid much attention to optimization, practitioners judge the robustness of the 'optimum' solution to be of greater importance.Therefore this paper proposes a practical methodology that is a stagewise combination of the following four proven techniques: (1)...

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,...

In practice, simulation analysts often change only one factor at a time, and use graphical analysis of the resulting Input/Output (I/O) data. The goal of this article is to change these traditional, naïve methods of design and analysis, because statistical theory proves that more information is...

This paper proposes a novel method to select an experimental design for interpolation in random simulation.(Though the paper focuses on Kriging, this method may also apply to other types of metamodels such as linear regression models.)Assuming that simulation requires much computer time, it is...