#### Filter Results:

- Full text PDF available (157)

#### Publication Year

1983

2017

- This year (2)
- Last 5 years (41)
- Last 10 years (103)

#### Publication Type

#### Co-author

#### Journals and Conferences

#### Key Phrases

Learn More

- Bruce E. Ankenman, Barry L. Nelson, Jeremy Staum
- 2008 Winter Simulation Conference
- 2008

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, interpolation-based metamodels of simulation output performance measures as functions of the controllable design or decision variables. To accomplish this we characterize… (More)

We describe a model for representing random vectors whose component random variables have arbitrary marginal distributions and correlation matrix, and describe how to generate data based upon this model for use in a stochastic simulation. The central idea is to transform a multivariate normal random vector into the desired random vector, so we refer to… (More)

- Marne C. Cario, Barry L. Nelson
- Oper. Res. Lett.
- 1996

We develop a model for representing stationary time series with arbitrary marginal distributions and autocorrelation structures and describe how to generate data based upon our model for use in a simulation.

- Barry L. Nelson, Julie L. Swann, David Goldsman, Wheyming Tina Song
- Operations Research
- 2001

In this paper, we address the problem of finding the simulated system with the best (maximum or minimum) expected performance when the number of alternatives is finite, but large enough that ranking-and-selection (R&S) procedures may require too much computation to be practical. Our approach is to use the data provided by the first stage of sampling in an… (More)

- L. Jeff Hong, Barry L. Nelson
- Operations Research
- 2006

We propose an optimization-via-simulation algorithm, called COMPASS, for use when the performance measure is estimated via a stochastic, discrete-event simulation, and the decision variables are integer ordered. We prove that COMPASS converges to the set of local optimal solutions with probability 1 for both terminating and steady-state simulation, and for… (More)

We describe the basic principles of ranking and selection, a collection of experimentdesign techniques for comparing “populations” with the goal of finding the best among them. We then describe the challenges and opportunities encountered in adapting ranking-and-selection techniques to stochastic simulation problems, along with key theorems, results and… (More)

- Barry L. Nelson
- Operations Research
- 1990

Other than common random numbers, control varlates is the most promising variance reduction technique in terms of its potential for widespread use: Control variates is applicable in single or multiple response simulation, it does not require altering the simulation run in any way, and any stochastic simulation contains potential control variates. A rich… (More)

- Seong-Hee Kim, Barry L. Nelson
- ACM Trans. Model. Comput. Simul.
- 2001

We present procedures for selecting the best or near-best of a finite number of simulated systems when best is defined by maximum or minimum expected performance. The procedures are appropriate when it is possible to repeatedly obtain small, incremental samples from each simulated system. The goal of such a sequential procedure is to eliminate, at an early… (More)

- Justin Boesel, Barry L. Nelson, Seong-Hee Kim
- Operations Research
- 2003

In this paper we address the problem of finding the simulated system with the best (maximum or minimum) expected performance when the number of systems is large and initial samples from each system have already been taken. This problem may be encountered when a heuristic search procedure—perhaps one originally designed for use in a deterministic… (More)