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Adaptive discretization of convex multistage stochastic programs

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Abstract

We propose a new scenario tree reduction algorithm for multistage stochastic programs, which integrates the reduction of a scenario tree into the solution process of the stochastic program. This allows to construct a scenario tree that is highly adapted on the optimization problem. The algorithm starts with a rough approximation of the original tree and locally refines this approximation as long as necessary. Promising numerical results for scenario tree reductions in the settings of portfolio management and power management with uncertain load are presented.

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Authors and Affiliations

  1. Department of Mathematics, Humboldt-University, 10099, Berlin, Germany

    Stefan Vigerske

  2. Niebuhrstraße 63, 10629, Berlin, Germany

    Ivo Nowak

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  1. Stefan Vigerske
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  2. Ivo Nowak
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Correspondence to Stefan Vigerske.

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Vigerske, S., Nowak, I. Adaptive discretization of convex multistage stochastic programs. Math Meth Oper Res 65, 361–383 (2007). https://doi.org/10.1007/s00186-006-0124-y

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  • DOI: https://doi.org/10.1007/s00186-006-0124-y

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