More Precise Decision-Making Methodology in the Temporalized Body of Evidence. Application in the Information Technology Management

Gia Sirbiladze (), Irina Khutsishvili, Otar Badagadze () and Mikheil Kapanadze ()
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Gia Sirbiladze: 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
Otar Badagadze: Department of Computer Sciences, Iv.Javakhishvili Tbilisi State University, University St. 13, 0186 Tbilisi, Georgia
Mikheil Kapanadze: Department of Computer Sciences, Iv.Javakhishvili Tbilisi State University, University St. 13, 0186 Tbilisi, Georgia

International Journal of Information Technology & Decision Making (IJITDM), 2016, vol. 15, issue 06, 1469-1502

Abstract: In this paper, we perform the analysis of temporalized structure of a body of evidence and possibilistic Extremal Fuzzy Dynamic System (EFDS) for the construction of more precise decisions based on the expert knowledge stream. The process of decision precision consists of two stages. In the first stage the relation of information precision is defined on a monotone sequence of bodies of evidence. The principle of negative imprecision is developed, as the maximum principle of knowledge ignorance measure of a body of evidence. Corresponding mathematical programming problem is constructed. On the output of the first stage we receive the expert knowledge precision stream of the criteria with respect to any decision. In the second stage the constructed stream is an input trajectory for the finite possibilistic model of EFDS. A genetic algorithm approach is developed for identifying of the EFDS finite model. The modelling process gives us the more precise decisions as a prediction of a temporalization procedure. The constructed technology is applied in the non-probabilistic utility theory for the information technology management problem.

Keywords: Theory of a body of evidence; fuzzy multi-attribute decision-making; aggregation operators; identification of a fuzzy dynamic system; fuzzy prediction; utility theory (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (1)

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DOI: 10.1142/S0219622016500371

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