A fully sequential procedure for indifference-zone selection in simulation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Statistical selection of the best system
Proceedings of the 33nd conference on Winter simulation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Selecting the best stochastic system for large scale problems in DEDS
Mathematics and Computers in Simulation
Statistical analysis of simulation output: output data analysis for simulations
Proceedings of the 34th conference on Winter simulation: exploring new frontiers
Selecting the best system: selecting the best system: theory and methods
Proceedings of the 35th conference on Winter simulation: driving innovation
Proceedings of the 35th conference on Winter simulation: driving innovation
Proceedings of the 35th conference on Winter simulation: driving innovation
Efficient simulation procedures: comparison with a standard via fully sequential procedures
Proceedings of the 35th conference on Winter simulation: driving innovation
Proceedings of the 35th conference on Winter simulation: driving innovation
Comparison with a standard via fully sequential procedures
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Solution quality of random search methods for discrete stochastic optimization
Mathematics and Computers in Simulation
Control variates for screening, selection, and estimation of the best
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Finding probably better system configurations quickly
SIGMETRICS '06/Performance '06 Proceedings of the joint international conference on Measurement and modeling of computer systems
WSC '04 Proceedings of the 36th conference on Winter simulation
Combined pattern search and ranking and selection for simulation optimization
WSC '04 Proceedings of the 36th conference on Winter simulation
WSC '04 Proceedings of the 36th conference on Winter simulation
Simulation of coherent risk measures
WSC '04 Proceedings of the 36th conference on Winter simulation
Statistical selection of the best system
WSC '05 Proceedings of the 37th conference on Winter simulation
Review of advanced methods for simulation output analysis
WSC '05 Proceedings of the 37th conference on Winter simulation
Using parallel and distributed computing to increase the capability of selection procedures
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
Performance of variance updating ranking and selection procedures
WSC '05 Proceedings of the 37th conference on Winter simulation
Application of multi-objective simulation-optimization techniques to inventory management problems
WSC '05 Proceedings of the 37th conference on Winter simulation
Simulation optimization with countably infinite feasible regions: Efficiency and convergence
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Finding probably best system configurations quickly
ACM SIGMETRICS Performance Evaluation Review
Proceedings of the 38th conference on Winter simulation
Combined ranking and selection with control variates
Proceedings of the 38th conference on Winter simulation
The "BEST" algorithm for solving stochastic mixed integer programs
Proceedings of the 38th conference on Winter simulation
Selection Procedures with Frequentist Expected Opportunity Cost Bounds
Operations Research
Optimizing system configurations quickly by guessing at the performance
Proceedings of the 2007 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
A framework for locally convergent random-search algorithms for discrete optimization via simulation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Recent advances in ranking and selection
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Using quantiles in ranking and selection procedures
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Differentiated service inventory optimization using nested partitions and MOCBA
Computers and Operations Research
Finding probably best systems quickly via simulations
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)
Simulation optimization using the cross-entropy method with optimal computing budget allocation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Finding feasible systems in the presence of constraints on multiple performance measures
ACM Transactions on Modeling and Computer Simulation (TOMACS)
A brief introduction to optimization via simulation
Winter Simulation Conference
Winter Simulation Conference
Simulation optimization with hybrid golden region search
Winter Simulation Conference
Selecting the best simulated system with weighted control-variate estimators
Mathematics and Computers in Simulation
Stochastic iterative dynamic programming: a Monte Carlo approach to dual control
Automatica (Journal of IFAC)
Efficient discrete optimization via simulation using stochastic kriging
Proceedings of the Winter Simulation Conference
Large-scale ranking and selection using cloud computing
Proceedings of the Winter Simulation Conference
Ordinal optimization: a nonparametric framework
Proceedings of the Winter Simulation Conference
Best-subset selection procedure
Proceedings of the Winter Simulation Conference
An Adaptive Hyperbox Algorithm for High-Dimensional Discrete Optimization via Simulation Problems
INFORMS Journal on Computing
Rapid Screening Procedures for Zero-One Optimization via Simulation
INFORMS Journal on Computing
Optimal learning for sequential sampling with non-parametric beliefs
Journal of Global Optimization
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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 R&S procedure to screen out alternatives that are not competitive, and thereby avoid the (typically much larger) second-stage sample for these systems. Our procedures represent a compromise between standard R&S procedures--which are easy to implement, but can be computationally inefficient--and fully sequential procedures--which can be statistically efficient, but are more difficult to implement and depend on more restrictive assumptions. We present a general theory for constructing combined screening and indifference-zone selection procedures, several specific procedures and a portion of an extensive empirical evaluation.