The objective of this Grant Opportunity for Academic Liaison with Industry (GOALI) award is to develop a framework for quantifying input uncertainty that is rigorously justified, but also useful. One of the most valuable aspects of stochastic simulation is its ability to characterize risk, where "risk" is the variability in a system's behavior. Unfortunately, there is a hidden and often substantial error in simulation that is present even if best practices for modeling, experimental design and output analysis are employed: input-uncertainty error. This research provides rigorously justified methods that account for input uncertainty that are also implementable within simulation software. The research displays the impact of input uncertainty via confidence intervals that quantify error and prediction intervals that quantify risk. The planned approach is to efficiently and accurately propagate input uncertainty from the input models to the simulation output using bootstrap resampling and recent advances in simulation metamodeling. The result will be a framework for quantifying input uncertainty that is rigorously justified, but also useful. The GOALI partner at Simio LLC will add expertise on simulation that exploits cloud computing, as well as providing a software test bed for the methods investigated by this research.
Input models are the driving processes in simulation experiments. They represent uncertainty at a level that resists more detailed modeling. Arrival processes in service and manufacturing simulations; demand processes in supply chain simulations; and patient occupancy times in hospital simulations are examples of inputs. Input models are based on observed real-world data, so they are subject to error. This error can overwhelm other sources of simulation error, placing users at risk of making critical and expensive decisions with unfounded confidence in (what appear to be) highly precise simulation assessments. This research will inform decision makers by quantifying this risk. Since input uncertainty is not well known or understood even in the academic community, the project plans ``teaching the teachers'' via introductory, advanced and vendor tutorials at the Winter Simulation Conference and elsewhere.
