Abstract
We consider the two-stage stochastic programming problem with recourse, and with a discretely distributed random variable with a finite number of realizations. When the number of realizations is large, the solution of these problems is difficult because the computation of values and subgradients of the expected recourse function is difficult. In this paper, we describe an algorithm that designs an upper bound to the expected recourse function. The computation of the values and subgradients of this upper bound is much faster than the computation of those of the expected recourse function, and is well-suited for parallel vector processors.
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References
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Ariyawansa, K.A. (1995). An Upper Bound Suitable for Parallel Vector Processing for the Objective Function in a Class of Stochastic Optimization Problems. In: Nash, S.G., Sofer, A., Stewart, W.R., Wasil, E.A. (eds) The Impact of Emerging Technologies on Computer Science and Operations Research. Operations Research/Computer Science Interfaces Series, vol 4. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-2223-2_1
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DOI: https://doi.org/10.1007/978-1-4615-2223-2_1
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