Browsing by Author "Prokhorchenko, Halyna"

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    Building Models to Optimize Vehicle Downtime in Multimodal Transportation
    (PC TECHNOLOGY CENTER, 2023) Razghonov, Serhii; Lesnikova, Iryna; Kuznetsov, Vitalii M.; Kuzmenko, Albina; Khalipova, Nataliіa; Chernikov, Danylo; Zvonarova, Olha V.; Prokhorchenko, Halyna; Horulia, Mykola; Bekh, Petro V.
    ENG: Sustainable development has become the main focus of transport policy and planning around the world. One of the practical goals when performing multimodal transportation is the optimization of logistics costs. That is, the object of research is the process of multimodal transportation. Empirical research shows that the problem of optimization of transportation costs can be solved by different methods. But the result will be similar. In the given approach, only one component of the transportation process is subject to optimization, which is the overload time. The solutions are based on the method of mass service theory and the method based on fuzzy logic. With the help of these methods, based on practical data, time parameters were calculated that characterize overloading from railway transport to road transport. The application of the method of a weakly formalized process in relation to transport logistics was considered, taking into account not only quantitative estimates but also qualitative, vaguely defined criteria that do not lend themselves to formalization, and the relationships between them. The model was developed for further research of this process, prediction of its behavior, optimization of functioning. It is based on the technology of fuzzy sets. The results obtained using the agent model based on the mass service network and the model based on fuzzy logic differ within the permissible specified limits of no more than 5–7 %. The application of fuzzy logic in the logistics of multimodal transportation is relevant and gives the best results compared to traditional methods of the theory of mass service systems. The article includes comparisons that reflect the advantages of the proposed approach. The obtained results are of a practical nature and can be used to make a decision on choosing a route and/or when transferring from one mode of transport to another.
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    Determining the Rational Motion Intensity of Train Traffic Flows on the Railway Corridors with Account for Balance of Expenses on Traction Resources and Cargo Owners
    (Sciendo, 2019) Butko, Tetiana V.; Muzykin, Mykhailo I.; Prokhorchenko, Andrii V.; Nesterenko, Halyna I.; Prokhorchenko, Halyna
    ENG: The article proposes a method for determining the rational motion intensity of specific train traffic flows on railway transport corridors with account for balance of expenses on traction resources and cargo owners. A mathematical model based on stochastic optimization is developed, which allows to optimize, in the conditions of risks, the interval between trailing trains on the railway lines taking into account the limited resources of the traction rolling stock, the capacity of the stations and freight fronts at the cargo destination point. Solving this mathematical model allows to find a balance between the expenses for movement of train traffic flows from different railway lines to their terminal reference station and the expenses of a consignee, subject to the limitations of the technological logistics chain in cargo transportation. For the solution of this mathematical model, a Real-coded Genetic Algorithm (RGA) was used.
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    Forecasting the Estimated Time of Arrival for a Cargo Dispatch Delivered by a Freight Train Along a Railway Section
    (НВП ПП «Технологічний Центр», Харьків, 2019) Prokhorchenko, Andrii V.; Panchenko, Artem; Parkhomenko, Larysa; Nesterenko, Halyna I.; Muzykin, Mykhailo I.; Prokhorchenko, Halyna; Kolisnyk, Alina
    ENG: This paper reports a method for predicting the expected time of arrival (ETA) of a cargo dispatch taking into consideration determining the duration at which a freight train travels along a railroad section where trains move not complying with a departure schedule. A characteristic feature of railroads with such a traffic system is the difficulty in predicting the stages of a transportation process, which necessitates the development of effective methods of forecasting. Based on correlation analysis, we have determined the dependence of the general macro-characteristics of train flow and individual parameters of a freight train on the duration of its movement along a section. It has been proposed to represent the dependence of predicted duration of train movement along a railroad section on the following factors: traffic intensity and density along a section, the proportion of passenger trains in total train flows, the length of a train and its gross weight. All experimental studies are based on actual data on the operation of the distance Osnova-Lyubotyn at the railroad network AO Ukrzaliznytsya. Based on a comparative analysis, using the indicators for accuracy and adequacy of several regression methods to predict ETA of cargo dispatch, we have chosen the regression model based on an artificial neural network MLP. To derive the MLP structure, a cross-validation method has been applied, which implies the validation of a mathematical model reliability based on the criteria of accuracy MAE and adequacy ‒ F-test. The structure of MLP has been obtained, which consists of five hidden layers. We predicted the time that it would take for a train to travel in facing direction along the Osnova-Lyubotyn section. For a given projection, the value for MAE was 0.0845, which is a rather high accuracy for this type of problems, and confirms the effectiveness of MLP application to solve the task on predicting a cargo dispatch ETA. The current study provides a possibility to design in the future an automated system for predicting a cargo dispatch ETA for a mixed-traffic railroad system in which freight trains depart not complying with a regulatory schedule.