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

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.
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Contributor : Florent Breuil <>
Submitted on : Wednesday, April 10, 2019 - 8:46:43 AM
Last modification on : Tuesday, November 24, 2020 - 11:42:03 AM



Simon Carladous, Jean-Marc Tacnet, Jean Dezert, Mireille Batton-Hubert. Decision-Aid Methods Based on Belief Function Theory with Application to Torrent Protection. Bossé É., Rogova G. Information Quality in Information Fusion and Decision Making. Information Fusion and Data Science, Springer, Cham, pp.329-357, 2019, 978-3-030-03643-0. ⟨10.1007/978-3-030-03643-0_15⟩. ⟨emse-02094823⟩



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