Stochastic programs without duality gaps
This paper studies dynamic stochastic optimization problems parametrizedby a random variable. Such problems arise in many applications in operations research and mathematical finance. We give sufficient conditionsfor the existence of solutions and the absence of a duality gap. Our proofuses extended dynamic programming equations, whose validity is established under new relaxed conditions that generalize certain no-arbitrageconditions from mathematical finance.
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