### Abstract

Original language | Undefined |
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Title of host publication | Proceedings of the 2006 Winter Simulation Conference, WSC'06 |

Publisher | WSC |

Pages | 398-405 |

Number of pages | 8 |

ISBN (Print) | 1424405017 |

Publication status | Published - Dec 2006 |

Event | 2006 Winter Simulation Conference - Monterey, United States Duration: 3 Dec 2006 → 6 Dec 2006 |

### Publication series

Name | |
---|---|

Publisher | WSC |

Number | 06EX1382C |

### Conference

Conference | 2006 Winter Simulation Conference |
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Abbreviated title | WSC 2006 |

Country | United States |

City | Monterey |

Period | 3/12/06 → 6/12/06 |

Other | 3 - 6 December 2006 |

### Keywords

- EWI-9066
- METIS-237909
- IR-66871

### Cite this

*Proceedings of the 2006 Winter Simulation Conference, WSC'06*(pp. 398-405). WSC.

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*Proceedings of the 2006 Winter Simulation Conference, WSC'06.*WSC, pp. 398-405, 2006 Winter Simulation Conference, Monterey, United States, 3/12/06.

**Efficient Simulation of Population Overflow in Parallel Queues.** / Nicola, V.F.; Zaburnenko, T.S.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Efficient Simulation of Population Overflow in Parallel Queues

AU - Nicola, V.F.

AU - Zaburnenko, T.S.

PY - 2006/12

Y1 - 2006/12

N2 - In this paper we propose a state-dependent importance sampling heuristic to estimate the probability of population overﬂow in networks of parallel queues. This heuristic approximates the “optimal��? state-dependent change of measure without the need for dif��?cult mathematical analysis or costly optimization involved in adaptive methodologies. Comprehensive simulations of networks with an arbitrary number of parallel queues and different traf��?c intensities yield asymptotically ef��?cient estimates (with relative error increasing sub-linearly in the overﬂow level) where no other state-independent importance sampling techniques are known to be ef��?cient. The ef��?ciency of the proposed heuristic surpasses those based on adaptive importance sampling algorithms, yet it is easier to determine and implement and scales better for large networks.

AB - In this paper we propose a state-dependent importance sampling heuristic to estimate the probability of population overﬂow in networks of parallel queues. This heuristic approximates the “optimal��? state-dependent change of measure without the need for dif��?cult mathematical analysis or costly optimization involved in adaptive methodologies. Comprehensive simulations of networks with an arbitrary number of parallel queues and different traf��?c intensities yield asymptotically ef��?cient estimates (with relative error increasing sub-linearly in the overﬂow level) where no other state-independent importance sampling techniques are known to be ef��?cient. The ef��?ciency of the proposed heuristic surpasses those based on adaptive importance sampling algorithms, yet it is easier to determine and implement and scales better for large networks.

KW - EWI-9066

KW - METIS-237909

KW - IR-66871

M3 - Conference contribution

SN - 1424405017

SP - 398

EP - 405

BT - Proceedings of the 2006 Winter Simulation Conference, WSC'06

PB - WSC

ER -