Abstract
This paper describes a serial and parallel implementation of a hybrid stochastic dynamic programming and progressive hedging algorithm. Numerical experiments show good speedups in the parallel implementation. In spite of this, our hybrid algorithm has difficulties competing with a pure stochastic dynamic programming approach on a given test case from macroeconomic control theory.
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This research has been conducted with financial support from the Norwegian Research Council. As most of this work was conducted under the TRACS program at the University of Edinburgh, we want to thank Ken McKinnon and all other helpful people at the Department of Mathematics and Statistics of Edinburgh University and at the Edinburgh Parallel Computing Centre. We are also very grateful to our colleague Stein W. Wallace for his continuing support of our work. Without him, this research would probably never have taken place. We would also like to thank an anonymous referee for helpful corrections and comments.
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Berland, N.J., Haugen, K.K. Mixing stochastic dynamic programming and scenario aggregation. Ann Oper Res 64, 1–19 (1996). https://doi.org/10.1007/BF02187638
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DOI: https://doi.org/10.1007/BF02187638