Building models to optimize vehicle downtime in multimodal transportation

Abstract

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