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12

MP
2008

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Stochastic programming approach to optimization under uncertainty

13 years 4 months ago

Stochastic programming approach to optimization under uncertainty

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In this paper we discuss computational complexity and risk averse approaches to two and multistage stochastic programming problems. We argue that two stage (say linear) stochastic programming problems can be solved with a reasonable accuracy by Monte Carlo sampling techniques while there are indications that complexity of multistage programs grows fast with increase of the number of stages. We discuss an extension of coherent risk measures to a multistage setting and, in particular, dynamic programming equations for such problems. Keywords Two and multistage stochastic programming

Alexander Shapiro

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MP 2008 | Multistage | Stochastic Programming | Stochastic Programming Problems |

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Added	13 Dec 2010
Updated	13 Dec 2010
Type	Journal
Year	2008
Where	MP
Authors	Alexander Shapiro

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