An Algorithm for Linear Stochastic Bilevel Problems - Charlotte Henkel
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Linear stochastic bilevel problems -although explained quickly- pose some difficulties when it comes to solving, even without the stochasticity. The aim of this work is to find a technique that allows for the use of decomposition methods known from stochastic programming in the framework of linear stochastic bilevel problems. The uncertainty is modeled as a discrete, finite distribution on some probability ... Full description
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Description
Linear stochastic bilevel problems -although explained quickly- pose some difficulties when it comes to solving, even without the stochasticity. The aim of this work is to find a technique that allows for the use of decomposition methods known from stochastic programming in the framework of linear stochastic bilevel problems. The uncertainty is modeled as a discrete, finite distribution on some probability space. Two approaches are made, one using the optimal value function of the lower level, whereas the second technique utilizes the Karush-Kuhn-Tucker conditions of the lower level. Using the latter approach, an integer-programming based algorithm for the global resolution of these problems is presented and evaluated.
More Information
| Author | Charlotte Henkel |
|---|---|
| Publisher | Südwestdeutscher Verlag für Hochschulschriften |
| Release year | 2015 |
| Cover type | Softcover |
| EAN | 9783838150376 |