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Information cascading in transportation management

Abstract

The purpose of the work is to study the use of information cascading in the management of transportation processes. The “complex transportation” model is studied. It includes multimodal transportation, intermodal transportation, transportation within the metropolis and in the suburbs of the metropolis. Complex transportation is characterized by a large amount of heterogeneous information. such an information complex often excludes the use of algorithmic methods for management. information cascading refers to decision support methods. This is a multiple heuristic method that reduces individual errors and non-rational alternatives. The difference between the design cascade model and the information cascade is shown. Two directions of application of the information cascade are described. Information cascading allows you to develop a more reliable transportation plan and accumulate experience in implementing transportation in difficult conditions.

About the Author

V. Ya. Tsvetkov
Russian University of Transport
Russian Federation

Doctor of Technical Sciences, Professor, Deputy Director for Science of the Law Institute of the Federal State Autonomous Educational Institution of Higher Education

Moscow, Obraztsova str., 9, building 9



References

1. Novikov A. N., Katunin A. A., Semkin A. N. Management of cargo transportation by road in modern conditions //Information technologies and innovations in transport. - 2015. – pp. 247-252.

2. Bodyul V. I., Feofilov A. N. Cargo transportation management system for railway rolling stock operators //Science and technology of transport. - 2012. – No. 1. – pp. 57-62.

3. Misharin A. S. Information technologies- the main condition for improving transportation management //Railway transport. – 2001. – №. 6. – Pp. 12-19.

4. Kozlov A.V. Multipurpose management of megalopolis transport //Science and Technology of Railways. – 2018. – Vol. 2. – №. 4 (8). – P. 40.

5. Kuzhelev P. D. Integrated management of a megapolis //Economic Consultant. – 2015. – №. 3 (11). – Pp. 14-18.

6. Nikiforov V. S. Multimodal transportation and transport logistics. - M.: TransLit. – 2007.

7. Mezentseva E. D., Prokhorova L. V. Multimodal transportation: features and risks // Society, economy, management. – 2021. – Vol. 6. – No. 1. – pp. 29-34.

8. Dominov D. R. Intermodal and multimodal transportation: definition and advantages // Academic research in modern science. – 2022. – Vol. 1. – no. 17. – pp. 300-304.Kudyan, S. G. Waste management: the principle of «one bucket» / S. G. Kudyan, A. I. Chernorubashkin // Solid household waste. – 2012. – № 5(71). – Pp. 54-57. – EDN OXFZPR.

9. Malyshev M. I. Review of research in the field of improving the efficiency of multimodal transportation based on technological solutions //Scientific Bulletin of the Moscow State Technical University of Civil Aviation. – 2020. – Vol. 23. – No. 4. – pp. 58-71.

10. Rondinelli D., Berry M. Multimodal transportation, logistics, and the environment: managing interactions in a global economy //European Management Journal. – 2000. – Vol. 18. – No. 4. – pp. 398-410.

11. https://en.wikipedia.org/wiki/Intermodal_freight_transport (date of application 20.10.2023).

12. Fu L., Sun D., Rilett L. R. Heuristic shortest path algorithms for transportation applications: State of the art //Computers & Operations Research. – 2006. – Vol. 33. – No. 11. – pp. 3324-3343.

13. Amaliah B., Fatichah C., Suryani E. A new heuristic method of finding the initial basic feasible solution to solve the transportation problem //Journal of King Saud University-Computer and Information Sciences. – 2022. – Vol. 34. – No. 5. – pp. 2298-2307.

14. Kengpol A., Tuammee S., Tuominen M. The development of a framework for route selection in multimodal transportation //The International Journal of Logistics Management. – 2014. – Vol. 25. – No. 3. – pp. 581-610.

15. Semenov V. V. Mathematical modeling of the dynamics of megalopolis traffic flows. - - M.: IPM im. MV Keldysh RAS. – 2004. – 44 p.

16. Maity G., Roy S. K., Verdegay J. L. Analyzing multimodal transportation problem and its application to artificial intelligence //Neural Computing and Applications. – 2020. – Vol. 32. – pp. 2243-2256.

17. Korolev E. A. «Cascade» model of information processes in the management system // Journal of new economy. – 2010. – №. 4 (30). – Pp. 5-22.

18. https://obzorposudy.ru/polezno/cto-znacit-kaskadirovat-informaciyu/ (date of application 12.09.23).

19. Zhou F. et al. A survey of information cascade analysis: Models, predictions, and recent advances //ACM Computing Surveys (CSUR). – 2021. – Т. 54. – №. 2. – P. 1-36.

20. Jalili M., Perc M. Information cascades in complex networks //Journal of Complex Networks. – 2017. – Т. 5. – №. 5. – P. 665-693.

21. https://dic.academic.ru/dic.nsf/socio/Трансмиссия. (date of application 14.09.23).

22. Mohamed Ahmed, Stella Spagna, Felipe Huici, and Saverio Niccolini. 2013. A peek into the future: Predicting the evolution of popularity in user generated content. In WSDM. 607-616.

23. Peng Cui, Shifei Jin, Linyun Yu, Fei Wang, Wenwu Zhu, and Shiqiang Yang. 2013. Cascading outbreak prediction in networks: A data-driven approach. In KDD. 901-909.


Review

For citations:


Tsvetkov V.Ya. Information cascading in transportation management. Logistics and Supply Chain Management. 2023;20(3):12-20. (In Russ.)

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