This paper studies the robust formulation of multi-stage stochastic models. We show that modeling paradigms based on Markowitz's single-stage model lead to non-optimal second-stage decisions. We present a non-convex formulation that enforces optimality. Returning to first principles, we explore a class of two-moment approximations to utility functions for two-stage systems. The resulting mathematical models are convex and can be extended easily to the multi-stage case.
By: A. J. King, S. Takriti, and S. Ahmed
Published in: RC20993 in 1997
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