Ranking of transport network development projects in the Sverdlovsk railroad area based on fuzzy logic

Relevance. Due to the turbulence of economic processes in the period of sanctions pressure on the economy, decisions should be made, effective, first of all, from a national position. For this purpose, it is necessary to justify them using multi-criteria and all available information, which at the initial stages is fundamentally incomplete, insufficiently reliable and sometimes weakly formalized. In such cases, it is advisable to use special methods to assess the decisions made in conditions of uncertainty, in particular methods of fuzzy logic and mathematics. Research objective. The study is aimed at assessing the order of priority of transport rail support on the investigated most important in the federal and regional scale main lines by including the most significant technological and economic criteria, reflecting the nationwide priority. Data and methods. To compare different methods of priority construction of the main lines of railway lines, we used the procedure of fuzzy multi-criteria analysis of the projects. The assumed priorities of transport rail support are based on four trunk line projects: the Middle Urals Latitudinal Railway on the N-Tagil - Perm section; the Troitsko-Pechorsk - Ivdel section; the Perm - Chernushka section; the Ust - Aha - Uray - Khanty-Mansiysk - Salym section. Results. The paper proves the possibility of applying the approach based on fuzzy logic to the analysis of economic processes in the period of shocks to the economy, caused, in particular, by the introduction of sanctions from unfriendly countries. The estimated priority of transport rail support on the four projects of the most important trunk lines is assessed. Conclusions. With the help of fuzzy logic methods, it is possible to find compromise options that satisfy the various interests of those affecting the decisions, regardless of the structural organization of the backbone industries, one of which is undoubtedly the transport industry.