## Abstract

Suppose that we want to compare k different systems, where μ_{i} denotes the steady-state mean performance of system i. Our goal is to use simulation to pick the 'best' system (i.e., the one with the largest or smallest steady-state mean). To do this, we present some two-stage procedures based on the method of batch means. Our procedures also construct multiple-comparisons-with-the-best (MCB) confidence intervals for μ_{i} - max_{j≠i} μ_{j}, i = 1,...,k. Under the assumption of an indifference zone of (absolute or relative) width δ, we can show that asymptotically (as δ → 0 with the size of the batches proportional to 1/δ^{2}), the joint probability of correctly selecting the best system and of the MCB confidence intervals simultaneously containing μ_{i} - max_{j≠i} μ_{j}, i = 1,...,k, is at least 1 - α, where α is prespecified by the user.

Original language | English (US) |
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Pages (from-to) | 362-366 |

Number of pages | 5 |

Journal | Winter Simulation Conference Proceedings |

DOIs | |

State | Published - 1995 |

Event | Proceedings of the 1995 Winter Simulation Conference, WSC'95 - Arlington, VA, USA Duration: Dec 3 1995 → Dec 6 1995 |

## All Science Journal Classification (ASJC) codes

- Software
- Modeling and Simulation
- Safety, Risk, Reliability and Quality
- Chemical Health and Safety
- Applied Mathematics