An alternative simulation budget allocation scheme for efficient simulation

We present an alternative simulation run allocation scheme for maximizing efficiency in simulation experiments for decision making under uncertainty. The issue of simulation efficiency is addressed from two perspectives: i) We want to minimize the total computation cost, with a constraint that the overall simulation quality must be higher than a desired level; ii) we would like to maximize the simulation quality with the constraint that the total computation cost can not exceed a given budget. While these two problems look different, we show that the solutions to these two problems are identical. Comparisons with other procedures show that our approach can achieve a speedup factor of 3~4 for a 10-design example. The speedup factor is even higher for problems having a larger number of designs. + Corresponding author: Professor Chun-Hung Chen, Dept. of Systems Engineering & Operations Research, George Mason University, 4400 University Drive, MS 4A6, Fairfax, VA 22030; Tel: 703-993-3572; Fax: 703993-1521; Email: [email protected]. ++ This work has been supported in part by NSF under Grants DMI-0002900, DMI-0049062 and IIS-0325074, by NASA Ames Research Center under Grants NAG-2-1565 and NAG-2-1643, by FAA under Grant 00-G-016, and by George Mason University Research Foundation.