Applying ER-MCDA and BF-TOPSIS to Decide on Effectiveness of Torrent Protection.

Lecture Notes in Artificial Intelligence(2016)

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摘要
Experts take into account several criteria to assess the effectiveness of torrential flood protection systems. In practice, scoring each criterion is imperfect. Each system is assessed choosing a qualitative class of effectiveness among several such classes (high, medium, low, no). Evidential Reasoning for Multi-Criteria Decision-Analysis (ER-MCDA) approach can help formalize this Multi-Criteria Decision-Making (MCDM) problem but only provides a coarse ranking of all systems. The recent Belief Function-based Technique for Order Preference by Similarity to Ideal Solution (BF-TOPSIS) methods give a finer ranking but are limited to perfect scoring of criteria. Our objective is to provide a coarse and a finer ranking of systems according to their effectiveness given the imperfect scoring of criteria. Therefore we propose to couple the two methods using an intermediary decision and a quantification transformation step. Given an actual MCDM problem, we apply the ER-MCDA and its coupling with BF-TOPSIS, showing that the final fine ranking is consistent with a previous coarse ranking in this case.
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关键词
Belief functions,BF-TOPSIS,ER-MCDA,Torrent protection
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