General-purpose simulation models of airside operations first became viable in the early 1980s and have been vested with increasingly sophisticated features since then. Three models currently dominate this field internationally: SIMMOD, The Airport Machine, and the Total Airport and Airspace Modeler (TAAM). A report by Odoni et al. (1997) contains detailed reviews (somewhat out-of-date by now) of these and several other airport and airspace simulation models and assesses the strengths and weaknesses of each. At their current state of development (and in the hands of expert users), they can be powerful tools in studying detailed airside design issues, such as figuring out the best way to remove an airside bottleneck or estimating the amount by which the capacity of an airport is reduced due to the crossing of active runways by taxiing aircraft. Unfortunately, these models are frequently misused in practice, at great cost to the client organization. This happens when they are applied to the study of “macroscopic” issues that can have only approximate answers because of the uncertainty inherent in the input data. An example is a question that often confronts airport operators: When will airside delays reach a level that will require a major expansion of an airport’s capacity (e.g., through the construction of a new runway)? Questions of this type, often requiring a look far into the future, are best answered through the approximate analytical models surveyed earlier, which permit easy exploration of a large number of alternative scenarios and hypotheses. Detailed simulation models, by contrast, cannot cope well with the massive uncertainty involved because they require inputs that are difficult to produce (e.g., a detailed schedule of aircraft movements at the airport for a
typical day 10 or 15 years hence) and lack credibility under the circumstances.