Temporalized Structure of Bodies of Evidence in the Multi-Criteria Decision-Making Model

Gia Sirbiladze (), Koba Gelashvili (), Irina Khutsishvili () and Anna Sikharulidze ()
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Gia Sirbiladze: Department of Computer Sciences, Iv. Javakhishvili Tbilisi State University, University St. 13, 0186 Tbilisi, Georgia
Koba Gelashvili: Department of Computer Sciences, Iv. Javakhishvili Tbilisi State University, University St. 13, 0186 Tbilisi, Georgia
Irina Khutsishvili: Department of Computer Sciences, Iv. Javakhishvili Tbilisi State University, University St. 13, 0186 Tbilisi, Georgia
Anna Sikharulidze: Department of Computer Sciences, Iv. Javakhishvili Tbilisi State University, University St. 13, 0186 Tbilisi, Georgia

International Journal of Information Technology & Decision Making (IJITDM), 2015, vol. 14, issue 03, 565-596

Abstract: In this paper, we perform the analysis of temporalized structure of bodies of evidence to construct more precise decisions based on the mathematical model of experts’ evaluations. The relation of information precision is defined on a monotone sequence of the bodies of evidence. For determining of a body of evidence the maximum principles of nonspecificity measure, the Shannon and Shapley entropies are applied. Corresponding mathematical programming problems are constructed. A new approach for the numerical solution of these problems is developed. The temporalized structure of bodies of evidence is used for precising the decision in the well-known Kaufmann’s theory of expertons. A measure of increase of decision precision is introduced, which takes into account all steps of temporalization. The temporalized method of expertons is applied to the problem of decision risk management, where the investment fund expert commission provides evaluation of competition results. In our specially created decision-making model, the goal of the expert technology is to aggregate and refine subjective evaluations provided by the expert commission members. The model performs as an adviser that assists the expert commission in selecting of decision with a minimum risks. The results of developed method are then compared with other well-known methods and aggregation operators such as: mean, median, ordered weighed averaging (OWA) and method of expertons.

Keywords: Fuzzy multi-criteria decision making; theory of a body of evidence; aggregation operator; modeling of uncertainty and imprecision; information precision relation; method of expertons (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (4)

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DOI: 10.1142/S021962201550008X

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