Methodological Expectations for Studies Using Computer Simulation

Simulation is often used in papers and studies across diverse fields like logistics, supply chains, health care, manufacturing, and defense. But simulations must be properly done, including input and model building, designing/analyzing the simulations, and model verification/validation. Unfortunately, simulation studies are not always done well, even though great effort could have gone into the model building and coding. This paper specifies, in brief outline, what authors and researchers need to do, when using simulation as a main tool, to build a convincing case for their findings and conclusions. Considerations on the input side of the model are enumerated, including specification of input distributions and processes; nonstationarity; random-number generation; and generating realizations of random variables and random processes. On the output side are issues of statistical analysis of simulation output; comparison, selection, and ranking of simulated scenarios; variance reduction; and optimum seeking. Involving matters on both the input and output sides are the essential activities of verification and validation. The intent is to establish expectations on what acceptable papers need to do if using simulation, and to serve as a guideline to applied simulation studies. Such papers and studies will then be more valid, more precise, more useful, and ultimately more convincing.