Computational efficiency of batching methods
Proceedings of the 29th conference on Winter simulation
A ranking and selection project: experiences from a university-industry collaboration
Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future - Volume 1
An asymptotic allocation for simultaneous simulation experiments
Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future - Volume 1
Batching methods for simulation output analysis: a stopping procedure based on phi-mixing conditions
Proceedings of the 32nd conference on Winter simulation
Simulation Modeling and Analysis
Simulation Modeling and Analysis
Mean Estimation Based on Phi-Mixing Sequences
SS '00 Proceedings of the 33rd Annual Simulation Symposium
Using common random numbers for indifference-zone selection
Proceedings of the 33nd conference on Winter simulation
Using Ordinal Optimization Approach to Improve Efficiency of Selection Procedures
Discrete Event Dynamic Systems
Recent advances in simulation optimization: a conservative adjustment to the ETSS procedure
Proceedings of the 34th conference on Winter simulation: exploring new frontiers
Indifference zone selection procedures: inferences from indifference-zone selection procedures
Proceedings of the 35th conference on Winter simulation: driving innovation
Enhancing evolutionary algorithms with statistical selection procedures for simulation optimization
WSC '05 Proceedings of the 37th conference on Winter simulation
OPEDo: a tool framework for modeling and optimization of stochastic models
valuetools '06 Proceedings of the 1st international conference on Performance evaluation methodolgies and tools
Simulation Allocation for Determining the Best Design in the Presence of Correlated Sampling
INFORMS Journal on Computing
Indifference-zone subset selection procedures: using sample means to improve efficiency
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
A multi-objective selection procedure of determining a Pareto set
Computers and Operations Research
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This paper discusses implementation of a two-stage procedure to determine the simulation run length for selecting the best of k designs. We purpose an Enhanced Two-Stage Selection (ETSS) procedure. The number of additional replications at the second stage for each design is determined by both the variances of the sample means and the differences of the sample means of alternative designs. We show that the ETSS procedure gives valid selections with significantly reduced simulation replications compared to Rinott's procedure. An experimental performance evaluation demonstrates the validity of the ETSS procedure.