DocumentCode :
402163
Title :
Better-than-optimal simulation run allocation?
Author :
Chen, Chun-Hung ; He, Donghai ; Yücesan, Enver
Author_Institution :
Dept. of Syst. Eng. & Operations Res., George Mason Univ., Fairfax, VA, USA
Volume :
1
fYear :
2003
fDate :
7-10 Dec. 2003
Firstpage :
490
Abstract :
Simulation is a popular tool for decision making. However, simulation efficiency is still a big concern particularly when multiple system designs must be simulated in order to find a best design. Simulation run allocation has emerged as an important research topic for simulation efficiency improvement. By allocating simulation runs in a more intelligent way, the total simulation time can be dramatically reduced. In this paper we develop a new simulation run allocation scheme. We compare the new approach with several different approaches. One benchmark approach assumes that the means and variances for all designs are known so that the theoretically optimal allocation can be found. It is interesting to observe that an approximation approach called OCBA does better than this theoretically optimal allocation. Moreover, a randomized version of OCBA may outperform OCBA in some cases.
Keywords :
computational complexity; decision making; digital simulation; optimisation; systems analysis; benchmark approach; decision making tool; design means; design variances; optimal allocation; randomized OCBA; simulation efficiency; simulation run allocation; simulation time reduction; system designs; Analytical models; Computational modeling; Context modeling; Costs; Decision making; Helium; Operations research; Sampling methods; Stochastic processes; Systems engineering and theory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Simulation Conference, 2003. Proceedings of the 2003 Winter
Print_ISBN :
0-7803-8131-9
Type :
conf
DOI :
10.1109/WSC.2003.1261460
Filename :
1261460
Link To Document :
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