A class of stochastic programs with decision dependent uncertainty
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Abstract
The standard approach to formulating stochastic programs is based on the assumption that the stochastic process is independent of the optimization decision. We address a class of problems where the optimization decisions influence the time of information discovery for a subset of the uncertain parameters. We extentd the standard modeling approach by presenting a disjunctive programming formulation that accommodates stochastic programs for this class of ploblems. A set of theoretical properties that lead to reduction in the size of the model is identified. A Lagrange duality based branch and bound algorithm is also presented.
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510 Mathematik
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Goel, Vikas, Grossmann, Ignacio E..(2004). A class of stochastic programs with decision dependent uncertainty. Stochastic Programming E-Print Series. , 2004,23. 10.18452/8327