### Mathematical Model  
The main conditions for the development of the route network are to estimate possible alternative routes between regions, and or ports and consignee locations, and to create preconditions for optimal route selection, assessing the best technical possibilities, the lowest possible energy consumption and acceptable economic conditions. A methodology for the cargo transportation optimization between regions, ports and consignee locations was developed on the basis of multi-criteria and comparison analysis. The main tasks of the developed methodology are based on the research on theoretical models, which can assist with finding optimal transportation modes, minimization energy requirements and practically useful applications. Considering at least one transport mode capacity (the number of containers transporting by train), it is possible to perform an analysis and find optimal solutions. Optimal solutions should include assessment of different transport modes time and the costs of transportation and energy requirements. The development of a sustainable transport system connecting regions and ports with delivery points is extremely important when analyzing various options for cargo delivery between regions and ports and vice versa. In many cases, the \"last mile\" problem that occurs when using different transport systems during transportation needs to be resolved. The \"Last mile\" in supply chain management and transportation planning, as well in this article, is the last leg of a journey comprising the movement of people and goods from a transportation hub or other loading/reloading place; for example, a railway station or inland waterways loading/unloading place, to a final destination. For the optimal development of the transport system, it is essential that it is sustainable in terms of time, cost and energy optimization. In this way, the function of comparing transports corridors and transport modes transport mode comparative index (\(K\)) can be expressed as follows:  
\[K=f(P,T.E\ldots) \tag{1}\]  
where: \(P\)--transportation price function; \(T\)--transportation time function; \(E\)--energy consumption function. Price function can be expressed via transportation lump sum costs (price on different parts of transportation) and the number transport units used, as follows:  
\[P=\frac{1}{\eta_{i}}[(P_{T}+P_{M1}+0,5\cdot P_{IM})N_{TUI1}+(0,5\cdot P_{IM}+ P_{M2}+P_{F})\cdot N_{TUI2}+\ldots] \tag{2}\]  
where: \(\eta_{i}\)--correlation coefficient, for the transport chain could be between 0.95 and 1.0; \(P_{T}\)--terminal price for one unit; \(P_{M1}\)--first chain part transport mode unit price; \(P_{IM}\)--intermodal terminal price; \(P_{M2}\)--second transport mode unit price; \(P_{F}\)--unit unloading price in final destination; \(N_{TUI1}\)--number of transport mode units on first chain part; \(N_{TUI2}\)--number of transport mode units on the second chain part; + \(\ldots\) --other possible elements, such as emission trading payments and so on. The 0.5 coefficient means there is an intermodal terminal price split in transport chain parts (delivery from port to intermodal terminal and delivery from intermodal terminal to final destination).