G-92-31
Algorithms for the Solution of Stochastic Dynamic Minimax Problems
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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.
Paru en août 1992 , 41 pages
Ce cahier a été révisé en septembre 1994