Optimization of the costs of a transport company in the implementation of multimodal transport

Reducing the costs of the transport company is one of the key issues in the management of the organization. There are standard ways to reduce the costs of transport companies, the article proposes options for reducing costs through the interaction of several modes of transport, namely, rail and road. The article discusses options for the transportation of goods by a trucking company. For the purpose of reducing operating costs, it is proposed to combine the use of road and rail transport on certain sections of the route of routes of various lengths. The authors made a conclusion about the dependence of the operating costs on the distance when using the above types of transport.

STUDYING ACTIVITIES OF COMPETITORS OF MOTOR TRANSPORT ENTERPRISE

This article discusses the study of competitors’ activity and presents some of the results of our research in this area. The main purpose of the study is to determine the positions, establish the strengths and weaknesses of their activities, assess their own ability to develop on this basis, the strategy and tactics of competitive behavior of the enterprise in the market. Based on the study of literature sources, the shortcomings of the existing model of analyzing competitors are identified, the proposals for its improvement are given. It is proposed to study the activities of competitors in the following sequence: identifying priority competitors, collecting data on their activities, identifying strengths and weaknesses, determining the position of the company among competitors. To determine the priority competitors, the analysis of the correlation field – the cell in the coordinate system – competitor and market segment is offered, in which we obtain the data: the volume of transport services, the market segment share, the share of traffic in total transport work. These indicators are determined for each competitor and show the priority of each competitor. At the first stage of the methodology of analysis of competitors’ activity, an approach to the definition of priority competitors is proposed, which means those of them who have the largest market share, both in the market as a whole and in a particular market segment. Much attention in the study is paid to determining the list of signs of competitors’ priority and establishing sources of information. On the basis of certain values of the enterprise and competitors there is an opportunity to establish the strengths and weaknesses of each of them. On the basis of the signs of enterprises’ activity that characterize their size, it is possible to obtain a generalized assessment of the market position of the trucking company and competitors, their strengths and weaknesses. At the same time, ratings are made without and with taking into account the importance of each criterion of the market position of MTE and competitors. The results of the research can be used in the process of determining the optimal strategy for motor transport enterprises.

Reengineering of business processes of a trucking company

As part of the domestic policy pursued in our country, state support for business contributes to the penetration of innovative activities into industrial enterprises. But, as practice shows, for an enterprise this is not a guarantee of increasing efficiency in the economic and social environment, despite the fact that the innovative projects being implemented have high potential. Often this is due to the fact that reengineering of business processes is not carried out or is not carried out effectively when introducing innovations. Innovations are superimposed on an unadopted and unprepared system of business processes, as a result of which a negative result is obtained. The reasons for the development of such events at the enterprise are the following aspects: an ambiguous understanding of the theoretical foundations of business process reengineering, innovation and innovation, and their features; the lack of an algorithm that allows efficient and effective reengineering of business processes when introducing innovations. In most organizations, as a rule, leaders use an intuitive approach when reengineering business processes and, as a result, this does not always end with success. Thus, there is a certain discrepancy between the need of economic agents for effective methods of reengineering business processes when introducing innovative technologies and an insufficient level of theoretical study of this issue. Also, issues of reengineering of business processes and issues of innovation, innovation in an unrelated context, separately relative to each other, are considered and studied.

Interterminal Truck Routing Optimization Using Deep Reinforcement Learning

The continued growth of the volume of global containerized transport necessitates that most of the major ports in the world improve port productivity by investing in more interconnected terminals. The development of the multiterminal system escalates the complexity of the container transport process and increases the demand for container exchange between different terminals within a port, known as interterminal transport (ITT). Trucks are still the primary modes of freight transportation to transport containers among most terminals. A trucking company needs to consider proper truck routing planning because, based on several studies, it played an essential role in coordinating ITT flows. Furthermore, optimal truck routing in the context of ITT significantly affects port productivity and efficiency. The study of deep reinforcement learning in truck routing optimization is still limited. In this study, we propose deep reinforcement learning to provide truck routes of a given container transport order by considering several significant factors such as order origin, destination, time window, and due date. To assess its performance, we compared between the proposed method and two approaches that are used to solve truck routing problems. The experiment results showed that the proposed method obtains considerably better results compared to the other algorithms.