论文信息 - A lagrangean duality based branch and bound for solving linear stochastic programs with decision dependent uncertainty

A lagrangean duality based branch and bound for solving linear stochastic programs with decision dependent uncertainty

Abstract We address a class of planning problems where the optimization decisions influence the time of information discovery for a subset of the uncertain parameters. The standard stochastic programming approach cannot be used for these problems. We present a hybrid mixed-integer disjunctive programming formulation and a Lagrangean duality based branch and bound algorithm for these problems and illustrate the advantages of this approach using examples for a manufacturing problem.

Vikas Goel | Ignacio E. Grossmann

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