Imitation forecast of railway system operation in a macroregion

Abstract

The article describes an analytical and information system that was used for forecasting the operation parameters of the railway system in a macroregion of Russia - the Far North. Its economy is focused on the extraction and processing of hydrocarbons, metal production, construction materials, and generate large volumes of exports and inter-regional cargo flows. The region covers an expansive territory and is characterized by harsh weather, an extreme environment, and uneven development of the transportation network. Research into the transportation issues of economic development in such areas presents a challenging task because the region is unique, statistical data are incomplete and classified; there is a hierarchy of businesses and organizations operating in the region that have their own goals and objectives and compete against its other; the region is plagued with social and environmental problems and a lack of administrative integration between individual districts. Using rigorous mathematical tools for assessing transportation infrastructure projects under such conditions is only limited to finding solutions to stand-alone problems and scenario comparison. A model of the applied system that is outlined in the article makes it possible to analyze specific projects of regional railway system development that take into account strategic priorities and goals of the state, social and economic development problems experienced by the neighboring regions, the oil and gas sector and major employers, as well as corporate goals of the sustainable development of railway companies. The application of the model over an extended period of time showed that the analysis of the structure of cargo flows and customers bound to junctions of the transportation network makes it possible to suggest what aspects of the railway infrastructure should be reorganized in line with the development dynamics of economic entities that consume transportation services. The study is built upon a number of projects that were implemented in the north of Tyumen Region and the Yamal- Nenets and Khanty-Mansi autonomous areas of Russia. © 2018 WIT Press.