Abstract
This doctor-thesis investigates how rail car fleet management depends on uncertainty in future demand. It is shown, that it's not correct to reduce uncertainty on standanard deviation or variance.
According to this, a definition for qualitiy of information is developed by using vertices and arc of a time-space transport network.
To optimzie network flow, an optimization model with a rolling planning horizon is created to show how network-flow costs depend on information quality. In numerous experiments the exakct relation ist investigated
Translated title of the contribution | Improving rail car fleet management by increasing the qualitiy of information about future demand |
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Original language | German |
Publication status | Published - 2001 |