Talal M Alkhamis
Department of Statistics & Operation Research,
Faculty of Science, Kuwait University,
P.O. Box 5969, Safat 13060, KUWAIT.
Simulation is an essential tool for performace evaluation of many practical engineering systems where engineers typically want to know how the system will perform for various parameter settings. Since large-scale simulation may require great amount of computer time and storage, appropriate statistical analysis can become quite costly. In this paper, we develop an interpolating technique as an effective tool for estimating system respones to parametric perturbations in simulation. We propose an interpolation technique where we can simulate at two parameters and , and interpolate the result for . In fact, we can interpolate results for an infinite number of values of . Using this technique the estimates have lower variance than those produced using Crude Monte Carlo simulation CMC. We are not limited to interpolating at two points. The proposed technique can be easily extended for more than two values of to produce interpolation estimates. We present computational results to show the validity of the proposed interpolation technique for sensitivity analysis in simulation.