GREEN SIMULATION OPTIMIZATION USING LIKELIHOOD RATIO ESTIMATORS
David J. Eckman, Miaomiao Feng · 2018
Green simulation is the reuse of past simulation outputs to enhance the efficiency of current and future simulation experiments. One natural application of green simulation is in the context of simulation optimization, wherein outputs from past iterations in a search can be reused in subsequent iterations. In this article, we draw attention to challenges that arise when green simulation likelihood ratio estimators are naively employed in simulation optimization. In particular, we show that for searches that identify new designs based on past outputs, outputs in different iterations are conditionally dependent, violating one of the assumptions for the validity of the likelihood ratio estimator. As a result, green simulation likelihood ratio estimators of the objective and gradient can become biased. We demonstrate how this conditional dependence and bias can adversely affect the behavior of gradient-based optimization algorithms.