Study on the Pricing and Path Scheme Comparison of Transit Freight
This paper aims to optimize the transportation network and transportation organization strategy of Transport through China, enabling operators to obtain greater profits, improving the efficiency of transit freight transport, and solving the problem of transportation pricing and route selection of transit goods. In this paper, the growth trend of transit transport demand is firstly determined. On this basis, the ultimate goal is to maximize the transport profit of the operator. In-depth analysis is made from the perspectives of transport income and transport cost. In addition, through combing existing international transportation routes, the overall transit network map of transit China to central Asian and European countries is drawn. In order to achieve the goal of minimizing transportation expenditure, the model of comparing freight routes is established. The customer is also classified by matrix model. Finally, with the transit transportation from Japan, Korea and other countries as examples, the model in this paper is verified, and the optimal transportation path is obtained through software solution. Compared with the current scheme, it has saved operating costs.
 Liu W, He M, & Sun Y, et al. (2009). Analysis of characteristics and influence factors of demands on transit transport. Eighth International Conference of Chinese Logistics and Transportation Professionals, 676-683.
 Nuzzolo A, Crisalli U, & Comi A. (2009). A demand model for international freight transport by road. European Transport Research Review, 1(1), 23-33.
 Ramūnas Palšaitis, Darius Bazaras, & Gintautas Labanauskas. (2004). The comparative analysis of lithuanian and latvian transit transport. Transport, 19(1), 9-14.
 Bulis A & Škapars R. (2013). Development of international freight transit in latvia. Procedia -Social and Behavioral Sciences, 99(6), 57-64.
 Almetova Z, Shepelev V, & Shepelev S. (2016). Cargo transit terminal locations according to the existing transport network configuration. Procedia Engineering, 150, 1396-1402.
 U. Brännlund, P. O. & Lindberg, A. NÕU, et al. (1998). Railway timetabling using lagrangian relaxation. Transportation Science, 32(4), 358-369.
 Anghinolfi D, Paolucci M, & Sacone S, et al. (2011). Integer programming and ant colony optimization for planning intermodal freight transportation operations. Automation Science and Engineering. IEEE, 214-219.
 Q. Meng, (2015). Itinerary provision and pricing in container liner shipping revenue management. Transportation Research Part E: Logistics and Transportation Review, 77, 135-146.
 Xie Y, Liang X, Ma L, et al. (2017). Empty container management and coordination in intermodal transport. European Journal of Operational Research, 257(1), 223-232.
 Martín E, Salvador J, & Saurí S. (2014). Storage pricing strategies for import container terminals under stochastic conditions. Transportation Research Part E: Logistics and Transportation Review, 68, 118-137.
 Crevier B, Cordeau J O, & Savard G. (2012). Integrated operations planning and revenue management for rail freight transportation. Transportation Research Part B: Methodological, 46(1), 100-119.
 G. Wilmsmeier, J. Monios, & B. Lambert. (2011). The directional development of intermodal freight corridors in relation to inland terminals. Journal of Transport Geography, 19, 1379–1386.
 Šakalys R, & Batarlienė N. (2017). Research on intermodal terminal interaction in international transport corridors. Procedia Engineering, 187, 281-288.
 Sui M, Shen F, & Wei H, et al. (2010). Logistics route planning with geographic data considering multiple factors. International Conference of Logistics Engineering and Management, 2346-2352.
 Ireland P, Case R, & Fallis J, et al. (2004). The Canadian pacific railway transforms operations by using models to develop its operating plans. Interfaces, 34(1), 5-14.