CAREER: Accounting for Information and Recourse in the Robust Design and Optimization of Stochastic Transportation Networks

University Of Texas At Austin, Austin TX

Investigators

Abstract

Networks form the core of countless problems in diverse fields of knowledge including transportation, communications, finance/economics, social interaction and many others. With the increasing capabilities of information technology and online control opportunities, each field has come to address the issue of network behavior under information in some manner, sometimes with vastly differing techniques. Further, the advances in sensor and information technology for many fields have occurred rapidly and have exceeded our methodological ability to fully model and plan for them. As a result of the relatively recent nature of these developments, it remains a pressing challenge to integrate and significantly enhance the knowledge from each field impacted by such advances. This CAREER development program addresses the problem of modeling information and online behavior in complex network systems in addition to developing approaches for designing such networks by leveraging the diverse existing methods to find commonalities and augmenting the methods with new problems and solution approaches. Newly introduced models in this CAREER program include the user equilibrium with recourse problem which describes the online behavior of all network travelers given information, interaction, and recourse opportunities. The new solution methods will consist of a combination of fundamental routing algorithm development, mathematical programming, and simulation techniques to address the key concepts of network behavior, information, recourse, dynamics, and uncertainty. The developments from this CAREER plan have the potential of advancing numerous fields that employ network modeling where online user behavior is important. Further, this program provides an opportunity to develop web-based learning tools, integrate vital aspects of behavior with information into the undergraduate and graduate curriculum, and continue outreach efforts to involve younger students in engineering. Often, network behavior is very counter-intuitive and it is even more so when online behavior and dynamics are considered. A continued effort will be made in this CAREER development program to improve the exposure students receive regarding the central methodologies and applications required to understand and appreciate the complexities of stochastic dynamic network behavior with information.