PROGRAMMING UNDER UNCERTAINTY AND STOCHASTIC OPTIMAL CONTROL
BOEING SCIENTIFIC RESEARCH LABS SEATTLE WA
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The theory of programming under uncertainty is extended to the case when the decision variables are elements of a Banach space. This approach leads to a very natural application of the computational techniques of mathematical programming to stochastic optimal control problems. It is shown that there exists an equivalent deterministic mathematical program whose set of feasible solutions is a convex set and whose objective function can be expressed as a convex function of the initial decision variables. In the second part, a duality theory is developed for this class of problems and some of the relations to the maximum principle for stochastic linear control problems are given.
- Operations Research