Selecting the best system: a decision-theoretic approach
Proceedings of the 29th conference on Winter simulation
New development of optimal computing budget allocation for discrete event simulation
Proceedings of the 29th conference on Winter simulation
A fully sequential procedure for indifference-zone selection in simulation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Simulation Modeling and Analysis
Simulation Modeling and Analysis
New Two-Stage and Sequential Procedures for Selecting the Best Simulated System
Operations Research
Comparisons with a Standard in Simulation Experiments
Management Science
Using Ranking and Selection to "Clean Up" after Simulation Optimization
Operations Research
Finding the best in the presence of a stochastic constraint
WSC '05 Proceedings of the 37th conference on Winter simulation
Performance evaluations of comparison-with-a-standard procedures
Proceedings of the 38th conference on Winter simulation
Two-phase screening procedure for simulation experiments
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Industrial strength COMPASS: A comprehensive algorithm and software for optimization via simulation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
INFORMS Journal on Computing
A brief introduction to optimization via simulation
Winter Simulation Conference
Value of information methods for pairwise sampling with correlations
Proceedings of the Winter Simulation Conference
Best-subset selection procedure
Proceedings of the Winter Simulation Conference
| Hi-index | 0.00 |
We develop fully sequential procedures for comparison with a standard. The goal is to find systems whose expected performance measures are larger or smaller than a single system referred to as a standard and, if there is any, to find the one with the largest or smallest performance. The general formulation of comparison with a standard gives the standard a special status and tries to protect it when its performance is better than or even equal to performance measures of all the other alternatives. Therefore, the problem cannot be formulated as the selection of the best and a specialized procedure is required. Our procedures allow for unequal variances across systems, the use of common random numbers, and known or unknown expected performance of the standard. Experimental results are provided to compare the efficiency of the procedure with other existing procedures.