Stopping Criterion for a Simulation-Based Optimization Method

We consider a new simulation-based optimization method called the Nested Partitions (NP) method. This method generates a Markov chain and solving the optimization problem is equivalent to maximizing the stationary distribution of this Markov chain over certain states. The method may therefore be considered a Monte Carlo sampler that samples from the stationary distribution. We show that the Markov chain converges geometrically fast to the true stationary distribution, and use these results to derive a stopping criterion for the method.

• Type: Conference
• Year: 1998
• Where: WSC
• Authors: Sigurdur Ólafsson, Leyuan Shi
• Keywords: Markov Chain, Modeling And Simulation, Simulation-based Optimization Method, Stationary Distribution, WSC 1998