INTELLECTUALIZATION OF MULTI-AGENT INTERACTION CONTROL DURING THE FREIGHT TRAFFIC ORGANIZATION IN PORTSIDE TRANSPORT SYSTEM

  • O.N. Chislov Rostov State Transport University
  • E.A. Mamaev Rostov State Transport University
  • M.V. Kolesnikov Rostov State Transport University
  • M.V. Bakalov Rostov State Transport University
  • V.M. Zadorozhniy
Keywords: Multi-agent interaction, operator, intellectualization, transport polygon, areas of influence, territorial picture, analytical curves

Abstract

Under the conditions of operation's and rolling stock owner’s plurality on the Russian railway
network the following issues are in case: excessive freight-hauling and carrying capacity of
section, oncoming rerun of empty boxcar in one type, excessive mileage of empty boxcars, sectional
speed reduction and others. More effective cooperation of transit process members based on
logistics, market simulation of freight traffics, creation of math models with the use of digitalization
and intellectualization methods of control are necessary for solving mentioned issues. This
study is devoted to research matters of principles updating modelling multi-agent interaction in
the portside transport systems. Methods of statistical, morphological, regression and system analysis,
mathematical and analytical modelling compose the methodological basis of the research.
Research and modelling characteristics of freight and car traffic flow distribution under contexts
of multiagency of transport complex, wherein the author-developed economic and geographical
method to delimit stations’ «spheres of influence» is applied allow to create analytical models of
transportation process based on integrated assessment of transport and technological infrastructure
of the railway polygon and cost of transport services. Building of a digital geographical model
of rolling stock distribution according to types of transportation service for portside stations by
analytic curves of higher order is one of special characteristics. «Spheres of influence» of loading
stations obtained by methods of economic and geographical delimitation allows formulating a
range of preferential directions while distributing car traffic. Acquired territorial scene of distributing
car traffic is a basis for solution of multi-attribute problem of optimization of boxcar directions
regulation taking into account multi-operator market of rolling stock, digitalization and intellectualization
of the branch. In addition to solution of objectives of transport services market
regulation in terms of rolling stock distribution, the problems of technological, economic, fiscaland digital interaction on a basis of logistics in the multi-agent systems are continued to be crucial.
Model and methodological propositions formed in this context should ensure reduction of
transport and logistic costs with parallel improvement of quantitative, qualitative and temporary
indicators of integrated logistic supply chains realization.

References

1. Mogale D.G., Cheikhrouhou N., Tiwari M.K. Modelling of sustainable food grain supply chain
distribution system: a bi-objective approach, International Journal of Production Research,
2020, Vol. 58, Issue 18, pp. 5521-5544.
2. Maiyar L.M., Thakkar J.J. Robust optimisation of sustainable food grain transportation with
uncertain supply and intentional disruptions, International Journal of Production Research,
2020, Vol. 58, Issue 18, pp. 5651-5675.
3. Knoop V., Hoogendoorn S. An Area-Aggregated Dynamic Traffic Simulation Mode, European
Journal of Transport and Infrastructure Research, 2015, No. 15 (2), pp. 226-242.
4. Wang X., Meng Q., Miao L. Delimiting port hinterlands based on intermodal network flows:
Model and algorithm, Transportation Research Part E: Logistics and Transportation Review,
2016, Vol. 88, pp. 32-51.
5. Levin B.A., TSvetkov V.Ya. Tsifrovaya zheleznaya doroga: printsipy i tekhnologii [Digital railway:
principles and technologies], Mir transporta [The world of transport], 2018, Vol. 16,
No. 3 (76), pp. 50-61.
6. Erofeev A.A., Borodin A.F. Kontseptsiya intellektual'nogo upravleniya perevozochnym
protsessom i etapnost' ee realizatsii [The concept of intelligent control of the transportation
process and the stages of its implementation], Problemy bezopasnosti na transporte: Mater. X
Mezhdunar. nauch.-prakt. konf. [Problems of safety in transport: materials of the X International
Scientific and Practical Conference]: In 5 part. Part 3, under the general ed.
Yu.I. Kulazhenko. Gomel': BelGUT, 2020, pp. 16-20.
7. Kupriyanovskiy V.P. i dr. Razvitie transportno-logisticheskikh otrasley Evropeyskogo Soyuza:
otkrytyy BIM, Internet Veshchey i kiber-fizicheskie sistemy [The development of transport and
logistics sectors of the European Union: an open BIM, Internet of Things and cyber-physical systems],
International Journal of Open Information Technologies, 2018, Vol. 6, No. 2, pp. 54-100.
8. Rozenberg E.N., Ozerov A.V., Lysikov M.G., Ol'shanskiy A.M. O perekhode k prediktivnomu
upravleniyu transportnymi sistemami s ispol'zovaniem Big Data [On the transition to predictive
management of transport systems using Big Data], Tekhnika zheleznykh dorog [Railway
Engineering], 2018, No. 1 (41), pp. 32-37.
9. Larin O.N., Kupriyanovskiy V.P. Voprosy transformatsii rynka transportno-logisticheskikh
uslug v usloviyakh tsifrovizatsii ekonomiki [Issues of transformation of the transport and logistics
services market in the conditions of digitalization of the economy], International Journal
of Open Information Technologies, 2018, Vol. 6, No. 3.
10. Alibekov B.I., Mamaev E.A. Mul'tiagentnye sistemy v logistike: informatsionno-analiticheskie
aspekty [Multi-agent systems in logistics: information and analytical aspects], Vestnik
Dagestanskogo gosudarstvennogo universiteta. Ser. 1. Estestvennye nauki [Bulletin of Dagestan
State University. Ser. 1. Natural Sciences], 2017, Vol. 32, Issue 4, pp. 56-62.
11. Bakalov M.V. Sistemnyy podkhod k voprosu vzaimodeystviya i konkurentsii v regional'noy
transportnoy sisteme [A systematic approach to the issue of cooperation and competition in the
regional transport system], Transport i logistika: strategicheskie prioritety, tekhno-logicheskie
platformy i resheniya v globalizovannoy tsifrovoy ekonomike: Sb. nauchnykh trudov III
mezhdunarodnoy nauchno-prakticheskoy konferentsii [Transport and logistics: strategic priorities,
technology platforms and solutions in the globalized digital economy: Collection of scientific
papers of the III international scientific-practical conference], 2019, pp. 36-39.
12. Os'minin A.T. O razrabotke intellektual'noy sistemy upravleniya perevozochnym protsessom
[On the development of an intelligent control system for the transportation process],
Zheleznodorozhnyy transport [Railway transport], 2021, No. 3, pp. 17-27.
13. Lyabakh N.N. Matematicheskiy instrumentariy issledovaniya zadach transporta i logistiki
cherez prizmu idey tsifrovoy ekonomiki [Mathematical tools for the study of transport and logistics
problems through the prism of the ideas of the digital economy], Transport i logistika:
strategicheskie prioritety, tekhnologicheskie platformy i resheniya v globalizovannoy tsifrovoy
ekonomike: Sb. nauch. trudov III mezhdunarodnoy nauchno-prakticheskoy konferentsii
[Transport and logistics: strategic priorities, technological platforms and solutions in the globalized
digital economy: A collection of scientific papers of the III International Scientific and
Practical Conference]. Rostov-on-Don: FGBOU VO RGUPS, 2019, pp. 217-221.
14. Chislov O.N., Zadorozhniy V.M., Bogachev V.A., Kravets A.S., Bogachev T.V., Bakalov M.V.
Mathematical modeling of cargo flow distribution in a regional multimodal transportation system,
Transport Problems, 2021, Vol. 16, No. 2, pp. 153-165.
15. Chislov O.N., Lyabakh N.N., Kolesnikov M.V., Bakalov M.V., Zadorozhniy V.M. Neyrosetevoe
issledovanie transportnykh sistem [Neural network research of transport systems], Nauchnoinformatsionnyy
sbornik «Transport: nauka, tekhnika, upravlenie» [Scientific and informational
collection "Transport: science, technology, management"]. VINITI RAN, 2021, No. 10, pp. 9-14.
16. Borodin A.F. Problemy kompleksnogo razvitiya zheleznodorozhnoy infrastruktury v
priportovykh transportnykh uzlakh [Problems of complex development of railway infrastructure
in port transport hubs], Transport Rossiyskoy Federatsii [Transport of the Russian Federation],
2017, No. 4 (71), pp. 45-50.
17. Rakhmangulov A., Muravev D., Hu H., Mishkurov P. Multi-agent optimization of the intermodal
terminal main parameters by using AnyLogic simulation platform: Case study on the
Ningbo-Zhoushan Port, International Journal of Information Management, 2021, Vol. 57,
pp. 102-133. DOI: 10.1016/j.ijinfomgt.2020.102133.
18. Tian W., Cao C. A generalized interval fuzzy mixed integer programming model for a multimodal
transportation problem under uncertainty, Engineering Optimization, 2017, Vol. 49, Issue 3,
pp. 481-498.
19. Sun Y., Liang X., Li X., Zhang C. A Fuzzy Programming Method for Modeling De-mand Uncertainty
in the Capacitated Road–Rail Multimodal Routing Problem with Time Windows, Journals Symmetry,
2019, Vol. 11, Issue 1, 91. Available at: https://doi.org/10.3390/sym11010091.
20. Aulin V., Lyashuk O., Pavlenko O., Velykodnyi D., Hrynkiv A., Lysenko S., Holub D., Vovk Y.,
Dzyura V., Sokol M. Realization of the Logistic Approach in the International Cargo Delivery
System, Communications - Scientific letters of the University of Zilina, 2020, Vol. 21 (No. 2),
pp. 3-12.
Published
2022-03-02
Section
SECTION II. CONTROL IN AVIATION, ROBOTIC AND TRANSPORT SYSTEMS