Abstract
Stochastic Dynamic Programming (SDP) is the method most extensively adopted to design release policies for water reservoir networks. However, it suffers of the well known “curse of dimensionality”, which actually limits its applicability to small reservoir networks. In this paper we present an on-line approach to policy design that not only constitutes a viable alternative to overcome the SDP limits, but can also be used with an inflow predictor to improve the performance of SDP-based off-line policies. This latter possibility is explored and discussed through a real world case study.
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