Please use this identifier to cite or link to this item:

Title: A new approach for parallel steady-state simulations
Authors: Hsieh, Ming-Hsiung
Contributors: 資管系
Keywords: Administrative data processing;Curve fitting;Discrete event simulation;Financial data processing;Least squares approximations;Confidence interval (CI);Discrete events;Generalized least square (GLS);Heavy traffics;new approaches;parallel processors;Property (S);Queue waiting;Steady state parameters;Steady-state simulations;Time length;Estimation
Date: 2006
Issue Date: 2015-07-21 15:05:36 (UTC+8)
Abstract: We propose a new procedure for building confidence interval estimators of steady-state parameters in discrete event simulations. The procedure uses parallel processors to generate independent replications and constructs the confidence interval estimator by solving a generalized least square problem. The most appealing theoretical feature of the proposed procedure is that the precision of the resulted estimator can be improved by simply increasing the number of processors (or independent replications) while the simulated time length is fixed on an appropriate level on each processor. Experiments conducted on M/M/1 queue waiting time processes in heavy traffic confirm this theoretical property. © 2006 IEEE.
Relation: Proceedings - Winter Simulation Conference, 論文編號 4117605, Pages 192-197
Data Type: conference
DOI 連結:
Appears in Collections:[資訊管理學系] 會議論文

Files in This Item:

File Description SizeFormat

All items in 學術集成 are protected by copyright, with all rights reserved.

社群 sharing