Irina Khutsishvili

Multistage decision-making fuzzy methodology for optimal investments based on experts’ evaluations

A new methodology of making a decision on an optimal investment in several projects is proposed. The methodology is based on experts’ evaluations and consists of three stages. In the first stage, Kaufmann’s expertons method is used to reduce a possibly large number of applicants for credit. Using the combined expert data, the credit risk level is determined for each project. Only the projects with low risks are selected.

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

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.

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

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.

Associated immediate probability intuitionistic fuzzy aggregations in MCDM

Abstract In this article, the Associated Immediate Probability Intuitionistic Fuzzy Order Weighted Averaging (As-IP-IFOWA) and the Associated Immediate Probability Intuitionistic Fuzzy Order Weighted Geometric (As-IP-IFOWG) operators are constructed. Associated probability distributions in the role of uncertainty measure are used. Arguments of the new aggregation operators are presented in the intuitionistic fuzzy values. Some properties of the constructed operators are presented. The conjugate intuitionistic fuzzy operator is defined. The conjugate connections between the constructed operators are shown. Several variants of the new operators for the decision making problem regarding assessment of the software development risks are used.