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Decision-Aid Methods Based on Belief Function Theory with Application to Torrent Protection

  • Simon CarladousEmail author
  • Jean-Marc Tacnet
  • Jean Dezert
  • Mireille Batton-Hubert
Chapter
Part of the Information Fusion and Data Science book series (IFDS)

Abstract

In mountainous areas, decision-makers must find the best solution to protect elements-at-torrential risk. The decision process involves several criteria and is based on imperfect information. Classical Multi-Criteria Decision-Aiding methods (MCDAs) are restricted to precise criteria evaluation for decision-making under a risky environment and suffer of rank reversal problems. To bridge these gaps, several MCDAs have been recently developed within belief function theory framework. The aims of this chapter are to introduce how these methods can be applied in practice and to introduce their general principles. To show their applicability to the real-life problem, we apply them to the Decision-Making Problem (DMP) comprising the comparison of several protective alternatives against torrential floods and selection of the most efficient one. We finally discuss the method improvements to promote their practical implementation.

Keywords

Decision under uncertainty Imperfect and conflicting information Multicriteria decision analysis Belief functions Risk analysis and mitigation Torrent protection 

Notes

Acknowledgements

This study was partially funded by the French Agricultural and Forest Ministry (MAA) and the French Environment Ministry (MTES).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Simon Carladous
    • 1
    Email author
  • Jean-Marc Tacnet
    • 2
  • Jean Dezert
    • 3
  • Mireille Batton-Hubert
    • 4
  1. 1.Département Risques Naturels (DRN)Office National des Forêts (ONF)GrenobleFrance
  2. 2.Snow Avalanche Engineering and Torrent Control Research Unit (ETNA)Université Grenoble Alpes, Irstea – UR ETGRSt-Martin d’Hères CedexFrance
  3. 3.ONERAThe French Aerospace LabPalaiseau CedexFrance
  4. 4.Institut Henri Fayol, UMR LIMOS 6158Ecole Nationale Supérieure des Mines de Saint-EtienneSaint-Etienne Cedex 2France

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