Abstract
The solution of a multistage stochastic programming problem needs a suitable representation of uncertainty which may be obtained through a satisfactory scenario tree construction. There is a trade-off between the level of accuracy in the description of the stochastic component and the computational tractability of the resulting scenario-based problem. In order to face such a trade-off which plays a crucial role in the determination of the optimal solution, we discuss methods that allow progressive reductions of a given scenario tree by means of spatial aggregation. In this process it is important to take into account the choice of proper aggregation criteria in order to try to preserve all the relevant information.
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© 2008 Springer, Milan
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Barro, D., Canestrelli, E., Ciurlia, P. (2008). Spatial Aggregation in Scenario Tree Reduction. In: Perna, C., Sibillo, M. (eds) Mathematical and Statistical Methods in Insurance and Finance. Springer, Milano. https://doi.org/10.1007/978-88-470-0704-8_4
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DOI: https://doi.org/10.1007/978-88-470-0704-8_4
Publisher Name: Springer, Milano
Print ISBN: 978-88-470-0703-1
Online ISBN: 978-88-470-0704-8
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