Bounds in Multistage Linear Stochastic Programming

Francesca Maggioni (), Elisabetta Allevi () and Marida Bertocchi ()
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Francesca Maggioni: Bergamo University
Elisabetta Allevi: Brescia University
Marida Bertocchi: Bergamo University

Journal of Optimization Theory and Applications, 2014, vol. 163, issue 1, No 10, 200-229

Abstract: Abstract Multistage stochastic programs, which involve sequences of decisions over time, are usually hard to solve in realistically sized problems. Providing bounds for optimal solution may help in evaluating whether it is worth the additional computations for the stochastic program vs. simplified approaches. In this paper we generalize measures from the two-stage case, based on different levels of available information, to the multistage stochastic programming problems. A set of theorems providing chains of inequalities among the new quantities are proved. Numerical results on a case study related to a simple transportation problem illustrate the described relationships.

Keywords: Multistage stochastic programming; Expected value problem; Value of stochastic solution; Skeleton solution (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (13)

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DOI: 10.1007/s10957-013-0450-1

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