This research will investigate the dynamics of storage systems, such as street networks, supply chains and transit lines. It will develop centralized and decentralized management methods that can prevent instabilities without undermining system performance. The work will focus on two difficult but related problems: (a) managing the morning commuting period in a congested city, and (b) stabilizing freight networks driven by inventory considerations. For the morning commute problem, centralized policies for congestion management such as tolls, taxation and land-use regulations will be designed and evaluated. For the freight network problem, decentralized inventory management policies will be developed that can eliminate the so-called "bullwhip effect" and approximately minimize cost. The research is important because it will help reduce the societal costs of congestion, and will show how to streamline supply chains and other storage networks. It will also show how generic tools can be developed for the control of these kinds of systems, which could encourage additional applications.
