This research has as its objective the development of effective algorithms for large-scale optimization models. The development includes both theoretical and computational investigation of decomposition techniques which allow division of the problem into more tractable subproblems. Of particular interest are models of large systems in which congestion or other nonlinearities are important. The methodology being investigated is applicable to many models that arise in operations research such as transportation planning, routing and scheduling, manufacturing, and logistics. It is also applicable to models of electrical and physical systems developed in other engineering disciplines and in the sciences.
