Abstract
In this chapter, we describe an application that was the theme of a research collaboration between an academic institution and a large company in charge of the production and distribution of electricity. We do not give an exhaustive description of the work that was done and of the decision-aiding tool that was developed. A detailed presentation of the first discussions, of the progressive formulation of the problem, of the assumptions chosen, of the hesitations and backtrackings, of the difficulties encountered, of the methodology adopted and of the resulting software would require nearly a whole book. Our purpose is to point out some characteristics of the problem, especially on the modelling of uncertainties. The description was thus voluntarily simplified and some aspects, of minor interest in the framework of this book, were neglected. The main purpose of this presentation is to show how difficult it is to build (or to improvise) a pragmatic decision model that is consistent and sound. It illustrates the interest and the importance of having well-studied formal models at our disposal when we are confronted with a decision problem. Sections 8.2 and 8.3 present the context of the application and the model that was established. Section 8.4 is based on a didactical example: it first illustrates and comments some traditional approaches that could have been used in the application; then it gives a detailed description of the approach that was applied in the concrete case.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2000 Springer Science+Business Media New York
About this chapter
Cite this chapter
Bouyssou, D., Marchant, T., Pirlot, M., Perny, P., Tsoukiàs, A., Vincke, P. (2000). Dealing with Uncertainty: An Example in Electricity Production Planning. In: Evaluation and Decision Models. International Series in Operations Research & Management Science, vol 32. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-1593-7_8
Download citation
DOI: https://doi.org/10.1007/978-1-4615-1593-7_8
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4613-5631-8
Online ISBN: 978-1-4615-1593-7
eBook Packages: Springer Book Archive