eng
Two Algorithms for Risk-averse Reformulation of Multi-stage Stochastic Programming Problems
nusl-386543
Šmíd, Martin
Kozmík, Václav
36th International Conference Mathematical Methods in Economics
Jindřichův Hradec (CZ)
20180912
GA16-01298S
GA ČR
2018
Multi-stage stochastic programming
deterministic equivalent
multi-period CVaR
nested CVaR
optimization algorithm
http://library.utia.cas.cz/separaty/2018/E/smid-0493316.pdf
http://hdl.handle.net/11104/0286991
http://www.nusl.cz/ntk/nusl-386543
Many real-life applications lead to risk-averse multi-stage stochastic problems, therefore effective solution of these problems is of great importance. Many tools can be used to their solution (GAMS, Coin-OR, APML or, for smaller problems, Excel), it is, however, mostly up to researcher to reformulate the problem into its deterministic equivalent. Moreover, such solutions are usually one-time, not easy to modify for different applications. We overcome these problems by providing a front-end software package, written in C++, which enables to enter problem definitions in a way close to their mathematical definition. Creating of a deterministic equivalent (and its solution) is up to the computer. In particular, our code is able to solve linear multi-stage with Multi-period Mean-CVaR or Nested Mean-CVaR criteria. In the present paper, we describe the algorithms, transforming these problems into their deterministic equivalents.
4 s.
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