This paper considers the possibility of devising a technology of fast railroad communication for the transportation of containers between the port and customer enterprises in the course of intermodal transportation. The purpose of technology development is to reduce the share of the use of trucks on intermodal routes and thus solve a number of related environmental, transport, municipal, and economic problems. The devised technology is based on the principles of bringing the railroad as close as possible to the end points of the route, minimizing the number of intermediate modes of transport, and enabling the maximum speed of movement of containers by rail. For this purpose, the use of MetroCargo™ freight terminals and CargoSprinter modular trains is proposed. In the course of the study, the task to reliably plan the operation of the fleet of such trains for the delivery of containers between the port and enterprises under the conditions of "noisy" initial data was set and solved. To this end, the problem was formalized in the form of a model of mixed programming, based on the principles of robust optimization. To optimize the model taking into consideration the principles of robustness, a procedure was proposed that uses a two-circuit genetic algorithm. As a result of the simulation, it was found that the resulting plan was only 6.5 % inferior to the objective criterion of the plan, which was compiled without taking into consideration robustness. It was proved that the devised model makes it possible to build an operational plan for the delivery of containers by rail, which is close to optimal. At the same time, the plan is implemented even in the case of the most unfavorable set of circumstances in the form of delays, shifts in the time windows of the cargo fronts, etc., that is, under the actual conditions of the transport process

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This paper has investigated the technology of forwarding local wagons at railroad technical stations and established the need to improve it given the extra downtime of local wagons. The main issue relates to the considerable combinatorial complexity of the tasks of operational planning. Another problem is that as part of the conventional approach, planning a station operation and planning a local operation at it is considered separately. Another planning issue is the lack of high-quality models for the preparation of initial data, in particular, data on the duration of technological operations, such as, for example, shunting operations involving local wagons forwarding. To resolve these issues, a new approach has been proposed, under which the tasks of operative planning of a technical station’s operation and its subsystem of local operations are tackled simultaneously, based on a single model. To this end, a mathematical model of vector combinatoric optimization has been built, which uses the criteria of total operating costs and wagon-hours spent at a station when forwarding local wagon flows, in the form of separate objective functions. Within this model, a predictive model was constructed in the form of a fuzzy inference system. This model is designed to determine the duration of shunting half-runs when executing the spotting/picking operations for delivering local wagons to enterprises’ goods sheds. The model provides for the accuracy level that would suffice at planning, in contrast to classical methods. A procedure has been devised for optimizing the planning model, which employs the modern genetic algorithm of vector optimization NSGA-III. This procedure is implemented in the form of software that makes it possible to build a rational operative plan for the operation of a technical station, including a subsystem of local operations, in graphic form, thereby reducing the operating costs by 5 % and the duration of maintenance of a local wagon by 8 %. The resulting effect could reduce the turnover time of a freight car in general on the railroad network, speed up the delivery of goods, and reduce the cost of transportation

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