Optimization over a finite number of system designs with one-stage sampling and multiple comparisons with the best

Authors:
Jason C. Hsu;Barry L. Nelson
Affiliations:
Department of Statistics, The Ohio State University, Columbus, Ohio;Department of Industrial and Systems Engineering, The Ohio State University, Columbus, Ohio
Venue:
WSC '88 Proceedings of the 20th conference on Winter simulation
Year:
1988

Citing 1
Cited 9

Optimization of stochastic systems

WSC '86 Proceedings of the 18th conference on Winter simulation

Multiple comparisons with the best for steady-state simulation

ACM Transactions on Modeling and Computer Simulation (TOMACS)
Robust multiple comparisons under common random numbers

ACM Transactions on Modeling and Computer Simulation (TOMACS)
A tutorial review of techniques for simulation optimization

WSC '94 Proceedings of the 26th conference on Winter simulation
Optimization of dispatching criteria for open-pit truck haulage system design using multiple comparisons with the best and common random numbers

WSC '93 Proceedings of the 25th conference on Winter simulation
Simulation optimization: methods and applications

Proceedings of the 29th conference on Winter simulation
A survey of ranking, selection, and multiple comparison procedures for discrete-event simulation

Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future - Volume 1
Batch-size effects on simulation optimization using multiple comparisons with the best

WSC' 90 Proceedings of the 22nd conference on Winter simulation
Simulation optimization: a survey of simulation optimization techniques and procedures

Proceedings of the 32nd conference on Winter simulation
Discrete-event simulation optimization using ranking, selection, and multiple comparison procedures: A survey

ACM Transactions on Modeling and Computer Simulation (TOMACS)

Quantified Score

Hi-index	0.00

Visualization

Abstract

Multiple comparisons with the best, which is applicable to single-stage experiments, is introduced as a method for choosing the best of a finite number of system designs. Examples are given.