Abstract
Problems relating to the carriage of goods are not out of date. Today they are implemented by rail, road, sea and river transport modes, each of which has advantages and disadvantages. Therefore, multimodal transport modes, which are difficult to manage, are becoming the most sought after. An important factor in the choice of mode of transport is its value, which also affects the price of the final product. The objective of the article was to construct a mathematical model of the generalized transport process for any mode of transport and for practically all types of cargo, allowing to estimate the time of operations and its cost. To this end, the article addresses the issue of the universality of transport operations. The differences are in the technical conditions of the individual processes that do not influence the modelling. The key role in this model is the timing of the operation. The simulation was carried out using Petri’s time stochastic networks. A simulation model has been built using the Business Studio platform to assess not only the timing of the operation but also the associated costs.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Egorov, A., Pilipchuk, N., Khmelev, I., Shatokhin, V., Kovkin, A.: World experience in the development of container traffic. IOP Conf. Ser. Mater. Sci. Eng. 698(6), 066050 (2019). https://doi.org/10.1088/1757-899X/698/6/066050
Gusev, N., Svatovskaya, L., Kucherenko, A.: The method of estimation of the technical conditions of transport facilities used in cold regions after the accidents caused by temperature anomalies. In: Petriaev, A., Konon, A. (eds.) Transportation Soil Engineering in Cold Regions, Volume 2. LNCE, vol. 50, pp. 309–318. Springer, Singapore (2020). https://doi.org/10.1007/978-981-15-0454-9_32
Moiseev, V.I., Ksenofontova, V.A.: mathematical model for cooling stratified hot oil in a railway tank. J. St. Petersburg State Univ. Technol. Des. Series 1 Nat. Technol. Sci. 1, 58–61 (2020). https://doi.org/10.46418/2079-8199_2020_1_9
Vorobiev, A.A., et al.: New way to increase the profitability of railway transportation of viscous petroleum products at low air temperatures. In: Problems of Mechanical Engineering. Proceedings of the V International Scientific and Technical Conference 218–226 (2021). https://doi.org/10.25206/978-5-8149-3246-4-2021-218-226
Vasco, D.A., Zambra, C., Nelson, O.: Moragad Numerical simulation of conjugate forced turbulent heat convection with induced natural laminar convection in a 2D inner cavity. Int. J. Thermal Sci. 87, 121–135 (2015). https://doi.org/10.1016/j.ijthermalsci.2014.08.008
Pokrovskaya, O., Orekhov, S., Kapustina, N., Kizyan, N.: Formation of logistics facilities in transport corridors. IOP Conf. Ser. Mater. Sci. Eng. 918(1), 012032 (2020). https://doi.org/10.1088/1757-899X/918/1/012032
Pokrovskaya, O., Fedorenko, R., Kizyan, N.: Cargo transportation and commodity flows management. IOP Conf. Ser. Mater. Sci. Eng. 918(1), 012050 (2020). https://doi.org/10.1088/1757-899X/918/1/012050
Kazemi, Y.: Modelling the Petroleum Supply Chain: Multimodal Transportation, Disruptions and Mitigation Strategies. State University of Agriculture and Applied Science, North Dakota (2016)
Saad, S.M., Elsaghier, E.H., Ezaga, D.: Planning and optimising petroleum supply chain. In: Proceedings of the 28th International Conference on Flexible Automation and Intelligent Manufacturing FAIM2018 (2018). https://doi.org/10.1016/j.promfg.2018.10.131
Farahani, M., Rahmani, D.: Production and distribution planning in petroleum supply chains regarding the impacts of gas injection and swap. Energy 141, 991–1003 (2017). https://doi.org/10.1016/j.energy.2017.10.013
Alirez, J.R., Moghadam, T., Jolai, F.: An evaluative continuous time Markov chain model for a three echelon supply chain with stochastic demand and lead time. IFAC-PapersOnLine 48(3), 248–253 (2015). https://doi.org/10.1016/j.ifacol.2015.06.089
Bushuev, N., Shulman, D., Sagajdak, K.: Modeling of container freight and passenger traffic. IOP Conf. Ser. Earth Environ. Sci. 403(1), 012226 (2019). https://doi.org/10.1088/1755-1315/403/1/012226
Karpova, T.S., Moiseev, V.I., Ksenofontova, V.A.: Construction of the simulation model of transportation oil products. In: CEUR Workshop Proceedings. Proceedings of Models and Methods of Information Systems Research Workshop 2019, pp. 103–107 (2019). http://ceur-ws.org/Vol-2556/paper18.pdf
Biswas, S., Narahari, Y.: Object oriented modeling and decision support for supply chains. In: Electronic Enterprises Laboratory, Computer Science and Automation, p. 560012Indian Institute of Science (2004). https://doi.org/10.1016/S0377-2217(02)00806-8
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Moiseev, V., Karpova, T., Ksenofontova, V. (2022). Generalized Transport Logistics Model. In: Manakov, A., Edigarian, A. (eds) International Scientific Siberian Transport Forum TransSiberia - 2021. TransSiberia 2021. Lecture Notes in Networks and Systems, vol 402. Springer, Cham. https://doi.org/10.1007/978-3-030-96380-4_85
Download citation
DOI: https://doi.org/10.1007/978-3-030-96380-4_85
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-96379-8
Online ISBN: 978-3-030-96380-4
eBook Packages: EngineeringEngineering (R0)