A COMPARISON OF VARIOUS VARIANCE REDUCTION TECHNIQUES VIS A VIS IMPORTANCE SAMPLING TO IMPROVE MONTECARLO SIMULATION.

With the rapid increase in computer technology and power, we need to develop such a technique which perform fast simulation and provide better result in least possible time. The Monte-Carlo (MC) simulation is widely used technique for simulation to obtain the results. By using MC technique, one get approximate answer quickly to a higher level of accuracy. But the major worrisome thing about the MC simulation is that, it provides approximation to the desired answer than the exact requirement which results an approximate error. Approximate error is the major factor taken into account whenever we evaluate answers. These approximation errors always effect the estimation of performance measure in Monte-Carlo simulation to a greater extent. In this paper, we discussed various variance reduction technique to overcome such type of error and show that how the Importance Sampling (IS) technique provide better approximation by reducing the variance to great extent as compared to other well-known techniques viz., Antithetic variable and Control Variate.