Group for Research in Decision Analysis

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.

, 41 pages

This cahier was revised in September 1994