Group for Research in Decision Analysis


Algorithms for the Solution of Stochastic Dynamic Minimax Problems


In this paper, we present algorithms for the solution of the dynamic minimax problem in stochastic programs. This dynamic minimax approach is suggested for the analysis of multi-stage stochastic decision problems when there is only partial knowledge on the joint probability distribution of the random data. The algorithms proposed in this paper are based on projected sub-gradient and bundle methods.

, 41 pages

This cahier was revised in September 1994