DocumentCode :
1740964
Title :
Ranking and selection for steady-state simulation
Author :
Goldsman, David ; Marshall, William S. ; Kim, Seong-Hee ; Nelson, Barry L.
Author_Institution :
Sch. of Ind. & Syst. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
Volume :
1
fYear :
2000
fDate :
2000
Firstpage :
544
Abstract :
We present and evaluate two ranking-and-selection procedures for use in steady-state simulation experiments when the goal is to find which among a finite number of alternative systems has the largest or smallest long-run average performance. Both procedures extend existing methods for independent and identically normally distributed observations to general stationary output processes, and both procedures are sequential
Keywords :
data analysis; digital simulation; normal distribution; stochastic processes; general stationary output processes; identically normally distributed observations; long-run average performance; ranking-and-selection procedures; sequential procedures; steady-state simulation; Analytical models; Engineering management; Gaussian distribution; H infinity control; Industrial engineering; Modeling; Random variables; Steady-state; Stochastic processes; Systems engineering and theory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Simulation Conference, 2000. Proceedings. Winter
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-6579-8
Type :
conf
DOI :
10.1109/WSC.2000.899762
Filename :
899762
Link To Document :
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