G-92-31
Algorithms for the Solution of Stochastic Dynamic Minimax Problems
and BibTeX reference
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.
Published August 1992 , 41 pages
This cahier was revised in September 1994