The relevance of the research topic is determined by the need to effectively solve multi-criteria decisionmaking problems in conditions of fuzzy information. In this regard, the creation of information technologies that would enable the user to select and use the most effective multi-criteria decision-making methods in conditions of fuzzy information is an important problem. The purpose of the study was to develop information technology for solving the multi-criteria decision-making problem using the modified Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) method based on the use of different metrics and the results of group expertise, which increases the reliability of the obtained decisions. Within the framework of the study, an analysis of the most popular multi-criteria decision-making methods, in particular, methods using the fuzzy set apparatus, was carried out. The article analyses different popular metrics for estimating the distances between a fuzzy positive ideal solution and a fuzzy negative ideal solution in the FTOPSIS method. A technique is proposed for comparing the results of applying different methods, in particular, FTOPSIS using triangular and trapezoidal fuzzy numbers, TOPSIS with triangular and trapezoidal fuzzy numbers for determining criteria weights, which makes it possible to analyse the scale of deviations between the obtained results and to assess the quality of the experts' work. The obtained results expand the possibilities of using TOPSIS and FTOPSIS methods for decision-making in conditions of multi-criteriality and uncertainty. As a practical application of the developed information technology and the modified FTOPSIS method, the article solves the problem of selecting the best of popular risk management standards in IT projects. This will increase the effectiveness of risk management in conditions of uncertainty and incompleteness of information, improve the validity of decisions made, as well as adapt the risk management process to specific conditions of each individual IT project
Maksymov et al. (Mon,) studied this question.