Aggregation and Discretization in Multistage Stochastic Programming
Daniel Kuhn
Department of Management Science and Engineering
Stanford University
Wednesday, February 15, 2006
4:30 - 5:45 PM
Terman Engineering Center, Room 453
Abstract:
Multistage stochastic programs have applications in many areas and
support policy makers in finding rational decisions that hedge against
unforeseen negative events. In order to ensure computational
tractability, continuous-state stochastic programs are usually
discretized; and frequently, the curse of dimensionality dictates that
decision stages must be aggregated. In this talk we construct two
discrete, stage-aggregated stochastic programs which provide upper and
lower bounds on the optimal value of the original problem. The
approximate problems involve finitely many decisions and constraints,
thus principally allowing for numerical solution.
Operations Research Colloquia: http://or.stanford.edu/oras_seminars.html