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• W2023821061 abstract "Multistage stochastic programs have applications in many areas and support policy makers in finding rational decisions that hedge against unforeseen negative events. In order to ensure computational tractability, continuous-state stochastic programs are usually discretized; and frequently, the curse of dimensionality dictates that decision stages must be aggregated. In this article we construct two discrete, stage-aggregated stochastic programs which provide upper and lower bounds on the optimal value of the original problem. The approximate problems involve finitely many decisions and constraints, thus principally allowing for numerical solution." @default.
• W2023821061 created "2016-06-24" @default.
• W2023821061 creator A5065780980 @default.
• W2023821061 date "2006-10-24" @default.
• W2023821061 modified "2023-10-14" @default.
• W2023821061 title "Aggregation and discretization in multistage stochastic programming" @default.
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• W2023821061 doi "https://doi.org/10.1007/s10107-006-0048-6" @default.
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