Determination of Weight Coefficients for Stochastic and Fuzzy Risks for Multimodal Transportation
Author(s) | |
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Nitsenko, Vitalii | Private Joint-Stock Company Higher education institution Interregional Academy of Personnel Management |
Kotenko, Sergiy | Institute of Market Problems and Economic-Ecological Research of the National Academy of Sciences of Ukraine |
Hanzhurenko, Iryna | Institute of Market Problems and Economic-Ecological Research of the National Academy of Sciences of Ukraine |
Date Issued |
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2020 |
. Research shows that the risks of multimodal transportation in the Northern ports of the Azov and Black seas, in real time, can vary by large quantities. This can cause significant problems for dynamic management of transportation, providing that transportation costs and time are minimized. Therefore, it is essential to formulate a mathematical model to determine the integral risk of freight traffic involved as it could help minimize the need for additional computer resources for the operation of logistics machinery. Determining the value of the integral risk is further complicated by the fact that the mathematical apparatus used for calculating stochastic and fuzzy risks tend to differ from one another. Therefore, an additional tool developed for the unification of various mathematical apparatus was done. The main task was conversion of local risks weight factors to components of integral risks, determined in actual time. The mathematical model has been tested for the dynamic management of freight traffic on the Black Sea ports - Mariupol, Odesa, Chornomorsk, Mikolaev, and Kherson. The route optimization was carried out for container and bulk cargoes, in particular, for grain cargoes. This allowed coverage for the whole range of risks that are inherent to multimodal transportation within the Azov-Black Sea region. The results confirmed that such an approach grants the possibility to choose routes with minimal transportation costs and time, as well as minimization of the use of computer resources.
Journal | Cite Score | SNIP | SJR | Year | Quartile |
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Journal of Physics: Conference Series | 0.7 | 0.464 | 0.21 | 2020 | Q4 |