Modeling issues when using simulation to test the performance of mathematical programming models under stochastic conditions

Discrete-event simulation (DES) models and discrete mathematical-programming optimization (DMPO) models are often used together in a variety of ways. This paper discusses the issues that modelers must address whe n using DES models to test the performance of DMPO models i n a stochastic environment. The issues arise during val idation of the simulation models – comparing the simulation re sults under deterministic conditions with results from de terministic optimization models. In our case, the issues are de ived from validating simulation models that are used to test the performance of scheduling and resource allocation m dels (integer and mixed-integer programming optimization models) under various types of uncertainty. The mod els are from our work in crossdocking operations; however, we believe they are relevant to a wide variety of prob lem domains. In addition to describing the issues, we o ffer suggestions on how modelers might address the conce rns.