Evaluating network analysis and agent based modeling for investigating the stability of commercial air carrier schedules.

摘要

For a number of years, the United States Federal Government has been formulating the Next Generation Air Transportation System plans for National Airspace System improvement. These improvements attempt to address air transportation holistically, but often address individual improvements in one arena such as ground or in-flight equipment.;In fact, air transportation system designers have had only limited success using traditional Operations Research and parametric modeling approaches in their analyses of innovative operations. They need a systemic methodology for modeling of safety-critical infrastructure that is comprehensive, objective, and sufficiently concrete, yet simple enough to be deployed with reasonable investment. The methodology must also be amenable to quantitative analysis so issues of system safety and stability can be rigorously addressed.;The literature suggests that both agent-based models and network analysis techniques may be useful for complex system development and analysis. The purpose of this research is to evaluate these two techniques as applied to analysis of commercial air carrier schedule (route) stability in daily operations, an important component of air transportation. Airline-like routing strategies are used to educe essential elements of applying the method. Two main models are developed, one investigating the network properties of the route structure, the other an Agent-based approach. The two methods are used to predict system properties at a macro-level. These findings are compared to observed route network performance measured by adherence to a schedule to provide validation of the results.;Those interested in complex system modeling are provided some indication as to when either or both of the techniques would be applicable. For aviation policy makers, the results point to a toolset capable of providing insight into the system behavior during the formative phases of development and transformation with relatively low investment. Both Agent-Based Modeling and Network Analysis were found to be useful in this context, particularly when applied with an eye towards the system context, and concentrated effort on capturing the salient features of the system of interest.