Acceptance sampling to aid in the verification of computational simulations

Abstract

Advances in computing allow for the construction of increasingly large and complex models and simulations. Exhaustive error checking of these intricate, large computational simulation models is daunting and potentially impractical. This paper explores an approach to error-checking simulation model components using an Acceptance Sampling methodology from the field of industrial manufacturing. We propose a systematic process in which a simulation inspector examines only a fraction of the computational model elements to measure the errors present. Our proposed process could support established verification processes by sampling the simulation components to identify whether the model is acceptably error free and which components require correcting. The proposed methodology relies on several statistical constraints but serves the interests of simulation professionals as part of the overall verification process. We illustrate the application and usefulness of our methodology through a real-world case study of a citywide microscopic transportation model.