A Descriptive Decision-making Model under Uncertainty Using Dempster-Shafer Theory and Prospect Theory
作者： Elhum Nusrat , Koichi Yamada
DOI: 10.14864/SOFTSCIS.2010.0.1504.0
关键词: Operator (computer programming) 、 Decision-making models 、 Decision problem 、 Operations research 、 Evidential reasoning approach 、 Econometrics 、 Dempster–Shafer theory 、 Set (abstract data type) 、 Mathematics 、 Prospect theory 、 Evidential decision theory
摘要: In this paper, a descriptive decision-making model under uncertainty has been introduced. At first, Evidential Decision Making Problem (EDMP) defined where Dempster-Shafer Theory used to represent uncertainty. Then we showed probability approximation approach of solving EDMP. For deciding the decision weights in different attitudes maker, have Ordered Weighted Averaging (OWA) operator. Later on, applied Prospect accomplish model. To show effectiveness our approach, also provided real life problem choosing job from set alternatives.
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