Game Theoretic Multidisciplinary Optimization Methods for System-of-Systems Analysis

Abstract

High-speed rail (HSR) planning models have not considered the response of airline operations to introducing high-speed rail to their commercial transportation networks. While considering the decision processes of travelers in predicting transportation system demand, HSR planning models have assumed airline response to be static; therefore, the overall objective of this research is to model and analyze travel demand in an intercity transportation system consisting of highway, conventional rail, air, and (possibly) high speed rail, for the purposes of anticipating system-wide shifts in travel demand resulting from the introduction of high-speed rail projects. In this dissertation, the approach to formulate, decompose, and solve this problem consists of the following tasks: (1) development of a computationally inexpensive model to estimate the interregional travel demand, performing model verification, uncertainty propagation, and sensitivity analysis. (2) Integration of the simplified surface transportation systems planning models with airline fleet optimization models to capture the optimal cooperative response of the aviation sector. (3) Apply the simplified models from objective 1 and the optimization methods from objective 2 to determine equilibrium resourcing and pricing conditions for competitive airlines given levels of service for HSR and airlines to determine the validity of pricing assumptions. These tasks are performed using the Cambridge Systematics travel demand model of the California Corridor.