Optimal importance sampling for Markovian systems

Importance sampling is a change-of-measure technique for speeding up the simulation of rare events in stochastic systems. In this paper the authors establish a number of properties characterizing optimal importance sampling measures for Markovian systems. The authors show how these properties may be used to compute the optimal measure and give specific results for a tandem queueing system. The authors´ approach has no apparent computational advantage over other direct methods, but it suggests a number of heuristic approximations which may lead to computationally attractive methods