Obtaining the optimal route for cargo transportation according to specified criteria is a laborious process for both shippers and forwarders, as it involves building routes, analyzing the route in accordance with specified criteria, calculating the final cost in accordance with the tariffs of carriers and transport zones, customs duties, additional services. Today there is no software solution that allows you to build an optimal logistics route using various modes of transport, as well as get all possible route options according to specified criteria. The article proposes the creation of a logistics navigator for freight transportation, defines its model in the form of a «black box», describes the input and output parameters of the navigator, defines the data that make up the reference information of the navigator necessary for analysis and decision-making, and defines the algorithm of the navigator. In conclusion, the advantages obtained from the implementation of the logistics navigator in the context of current problems and such promising solutions as the implementation of intelligent analysis of the flows of transport corridors by type of transport and cargo, forecasting the loading of infrastructure facilities, expanding the functionality of the logistics navigator to collect analytics on the state of transport infrastructure facilities are formulated. authorities. The regulations and reference books regulating the process of cargo transportation for aviation, sea, rail and road modes of transport, classifiers in various automated systems for working with transportation documents are studied, the classification of objects of regulatory and reference information of the logistics navigator is made, the context of the application of various objects of regulatory and reference information is described. As a result of the study, the structure of the regulatory and reference information of the logistics navigator was built, the logic for solving the problem of finding the optimal route and calculating the cost of transportation was determined.

The purpose of the work is to study the use of information cascading in the management of transportation processes. The “complex transportation” model is studied. It includes multimodal transportation, intermodal transportation, transportation within the metropolis and in the suburbs of the metropolis. Complex transportation is characterized by a large amount of heterogeneous information. such an information complex often excludes the use of algorithmic methods for management. information cascading refers to decision support methods. This is a multiple heuristic method that reduces individual errors and non-rational alternatives. The difference between the design cascade model and the information cascade is shown. Two directions of application of the information cascade are described. Information cascading allows you to develop a more reliable transportation plan and accumulate experience in implementing transportation in difficult conditions.

In the modern world increasingly arise the question of the modernizing legacy software written using non-modern programming paradigms and an old language standard that is not supported by modern compilers. If you use a different, modern, more expressive programming language to “rewrite”, you need to not just modernize, but rather rewrite a program that will use the functionality of the old software. The such a task difficulty lies in the testing methods absent in the legacy code, which potentially leads to errors in the new software. The author, using the example of working on a new system that uses the functionality of an old proven system, shows the advantages of using test-driven development technology.

The article explores the temporal approach applicable to solving logistics problems. Temporal models, temporal relations, temporal marks are considered. The article introduces the concept of “temporal analysis”. A taxonomy of temporal models is given. Temporal analysis combines temporal logic and temporal modeling. Temporal cause-and-effect analysis is described as a development of temporal analysis. The content of the concept of temporary uncertainty is revealed. The connection between temporal models and situational models is shown. The features of the use of temporal methods in transport management are described. The features of the use of temporal models in the field of transport are described. The article provides an analysis of time intervals. The concept of local time interval and interval boundaries is introduced. The features of obtaining and using timestamps are described. A formalized description of temporal models is given. The connection of temporal intervals with situations and states of the object is shown. The article gives a formal description of near and distant intervals. Three temporal models of movement are given. The article reveals the content of temporal cause-andeffect analysis. The reasons for its appearance are shown. Methods for reducing temporal uncertainty are described.

The article considers the existing principles and procedure for planning the needs of the locomotive fleet of freight traffic used on the railway network of JSC «Russian Railways» at the present time and suggests a variant of the development of the planning system.

The article presents the results of the development of models and methods for solving problems aimed at scientifically sound proposals aimed at the formation of comprehensive measures to improve the efficiency of infrastructure use and increase the carrying capacity of landfills of Russian railways. The main provisions of the developed Passport of the investment project for the modernization of the railway infrastructure of the Eastern polygon (the second stage) are considered. The main provisions of the program for the phased withdrawal of the track complex of JSC «Russian Railways» to the regulatory level by 2030 are presented. The changes in the order of calculation of throughput and carrying capacity in the light of the release of the new Instructions are analyzed. The expected effects from the application of the new Instruction are formulated. The technology of calculating the risks of non-development of transportation according to the options for organizing a repair and travel campaign (for long-term and medium-term periods) is given, as well as measures to reduce these risks are summarized.