Ranking and selection for steady-state simulation

Authors:
David Goldsman;William S. Marshall;Seong-Hee Kim;Barry L. Nelson
Affiliations:
Georgia Institute of Technology, Atlanta, GA;Georgia Institute of Technology, Atlanta, GA;Northwestern University, Evanston, IL;Northwestern University, Evanston, IL
Venue:
Proceedings of the 32nd conference on Winter simulation
Year:
2000

Citing 11
Cited 7

Restricted subset selection procedures for simulation

Operations Research
Properties of standardized time series weighted area variance estimators

Management Science
Strong consistency of the variance estimator in steady-state simulation output analysis

Mathematics of Operations Research
Optimal mean-squared-error batch sizes

Management Science
Selecting the best system in steady-state simulations using batch means

WSC '95 Proceedings of the 27th conference on Winter simulation
Ranking and selection procedures using standardized time series

WSC '85 Proceedings of the 17th conference on Winter simulation
Two-stage procedures for multiple comparisons with a control in steady-state simulations

WSC '96 Proceedings of the 28th conference on Winter simulation
Two-stage multiple-comparison procedures for steady-state simulations

ACM Transactions on Modeling and Computer Simulation (TOMACS)
A fully sequential procedure for indifference-zone selection in simulation

ACM Transactions on Modeling and Computer Simulation (TOMACS)
Ranking and selection in simulation

WSC '83 Proceedings of the 15th conference on Winter Simulation - Volume 2
Overlapping batch means: something for nothing?

WSC '84 Proceedings of the 16th conference on Winter simulation

Statistical analysis of simulation output: output data analysis for simulations

Proceedings of the 34th conference on Winter simulation: exploring new frontiers
Review of advanced methods for simulation output analysis

WSC '05 Proceedings of the 37th conference on Winter simulation
Finding the best in the presence of a stochastic constraint

WSC '05 Proceedings of the 37th conference on Winter simulation
On the Asymptotic Validity of Fully Sequential Selection Procedures for Steady-State Simulation

Operations Research
A combined procedure for discrete simulation---optimization problems based on the simulated annealing framework

Computational Optimization and Applications
A Procedure for Generating Batch-Means Confidence Intervals for Simulation: Checking Independence and Normality

Simulation
ADAPT Selection procedures to process correlated and non-normal data with batch means

Winter Simulation Conference

Quantified Score

Hi-index	0.00

Visualization

Abstract

We present and evaluate two ranking-and-selection procedures for use in steady-state simulation experiments when the goal is to find which among a finite number of alternative systems has the largest or smallest long-run average performance. Both procedures extend existing methods for independent and identically normally distributed observations to general stationary output processes, and both procedures are sequential.