Abstract
Methodological approaches to assessing the prospects for the development of port transport and technological systems in terms of interaction management in the “railway station - port” system are investigated. The issues of updating clustering methods and time parameterization in the management of cargo flows of port transport systems at a new stage of development with the prospect of their application in intelligent control systems for the selection of rational schemes for the transportation process operation are considered. Three types of clusters are proposed that function within the boundaries of the regional port transport and technological system, and include homogeneous objects or objects performing a single transport function: a loading cluster, a single port cluster and a port cluster. To form the analytical model of cargo flow management based on the principles of time parameterization, criteria for the rationality of transport processes have been determined for the minimum demurrage time of the rolling stock in the transport system, the minimum number of transport processes when performing the maximum amount of work, and the maximum speed of transport processes with the values of rational loading of infrastructure facilities of the transport system.
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References
Mogale DG, Cheikhrouhou N, Tiwari MK (2020) Modelling of sustainable food grain supply chain distribution system: a bi-objective approach. Int J Prod Res 58(18):521–5544
Maiyar LM, Thakkar JJ (2020) Robust optimisation of sustainable food grain transportation with uncertain supply and intentional disruptions. Int J Prod Res 58(18):5651–5675
Gao Y, Yang L, Li S (2016) Uncertain models on railway transportation planning problem. Appl Math Model 40(7–8):4921–4934
Tian W, Cao C (2017) A generalized interval fuzzy mixed integer programming model for a multimodal transportation problem under uncertainty. Eng Optim 49(3):481–498
Sun Y, Liang X, Li X, Zhang C (2019) A fuzzy programming method for modeling demand uncertainty in the capacitated road-rail multimodal routing problem with time windows. J Symmetry 11(1):91. https://doi.org/10.3390/sym11010091
Aulin V, Lyashuk O, Pavlenko O et al (2020) Realization of the logistic approach in the international cargo delivery system. Commun Sci Lett Univ Zilina 21(2):3–12
Prachi A, Talari G (2018) Multi-choice stochastic transportation problem involving logistic distribution. Adv Appl Math Sci 18(1):45–58
Wiradanti B, Pettit S, Potter A, Abouarghoub W (2018) Ports, peripherality and concentration – deconcentration factors: a review. Marit Bus Rev. https://doi.org/10.1108/MABR-09-2018-0040
Valls J, Langen P, Garcia-Alonso L et al (2020) Understanding port choice determinants and port hinterlands: findings from an empirical analysis of Spain. Marit Econ Logist 22:53–67
Chislov ON, Bogachev VA, Zadorozhniy VM et al (2019) Modelling of the rail freight traffic by the method of economic-geographical delimitation in the region of the South-Easter Coast of the Baltic Sea. Transp Probl 14(2):77–87
Chislov O, Bogachev T, Kravets A, Bogachev V, Zadorozhniy V, Egorova I (2020) Time parameters optimization of the export grain traffic in the port railway transport technology system. In: Sierpiński G (eds) Smart and green solutions for transport systems (TSTP 2019). Advances in Intelligent Systems and Computing, vol 1091, pp 126–137
Meng F, Zhang Z, Hou X (2019) Machine learning for prediction of sudden cardiac death in heart failure patients with low left ventricular ejection fraction: study protocol for a retroprospective multicentre registry in China. BMJ Open 9:e023724. https://doi.org/10.1136/bmjopen-2018-023724
Kolesnikov MV, Lyabakh NN, Mamaev EA, Bakalov MV (2020) Efficient and secure logistics transportation system. In: VIII International Scientific Conference Transport of Siberia 2020, vol 918, p 012031. IOP Conf Ser Mater Sci Eng. IOP Publishing. https://doi.org/10.1088/1757-899X/918/1/012031
Rozewsky P, Novikov D, Zaikin O, Bakhtadze N (eds) (2016) Incentive mechanisms for multi-agent organizational systems. New frontiers in information and production systems modeling and analysis – incentive mechanisms, competence management, knowledge-based production. Series “Intelligent Systems Reference Library”, vol 268, pps 35–57. Springer, Berlin
Lyabakh N, Saryan A, Dergacheva I et al (2020) Development of the pattern recognition theory for solving the tasks of object classification and yard processes. Adv Intell Syst Comput 1226:59–68
Acknowledgements
The reported study was funded by RFBR, Sirius University of Science and Technology, JSC Russian Railways and Educational Fund «Talent and success», project number 20-38-51014.
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Chislov, O., Magomedova, N., Kravets, A., Bezusov, D., Zadorozhniy, V. (2022). Clustering Methods and Time Parameterization in the Management of Port Cargo Flows. In: Mottaeva, A. (eds) Technological Advancements in Construction. Lecture Notes in Civil Engineering, vol 180. Springer, Cham. https://doi.org/10.1007/978-3-030-83917-8_25
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DOI: https://doi.org/10.1007/978-3-030-83917-8_25
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