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Two Algorithms for Risk-averse Reformulation of Multi-stage Stochastic Programming Problems

Conference Paper (international conference)

Šmíd Martin, Kozmík Václav


serial: 36th International Conference Mathematical Methods in Economics, p. 551-554 , Eds: Váchová Lucie, Kratochvíl Václav

action: 36th International Conference Mathematical Methods in Economics, (Jindřichův Hradec, CZ, 20180912)

project(s): GA16-01298S, GA ČR

keywords: Multi-stage stochastic programming, deterministic equivalent, multi-period CVaR, nested CVaR, optimization algorithm

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abstract (eng):

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.

RIV: AH

2012-12-21 16:10