Development of digital platforms for the functioning of logistics networks

The proposed work is a continuation of research aimed at developing algorithms embedded in the servers of integrated platforms for the functioning of logistics network processes, and in demand in the tasks of forming a stable digital environment. Based on the principles laid down in the concept of Industry 4.0, all modern software solutions are built on the basis of complex mathematical models that play the role of digital twins. Only in this way is the main goal achieved — the search for an optimal management solution. The logistics tasks currently under consideration, as a rule, were formulated only as one-dimensional supply chains or simple tasks of forming consumer value on mathematical graphs, in the form of which the image of network logistics and commercial structures is presented. The trend towards digitalization and the introduction of artificial intelligence systems at the stage of managerial decision-making, which is necessary for sustainable work in a competitive environment, dictates the need to create algorithms and models that much more adequately reflect the essence of real processes and are as relevant as possible both in economic and technological aspects. The results of this study allow us to take into account an additional important factor of the multidimensionality of the displacement processes. This circumstance is always present when moving continuous flows between nodes of the logistics network, and is also, as a rule, characteristic of discrete flows.

Keywords: digitalization, network-like n-dimensional domain, logistics, initial boundary value problem, semi-discretization method, algorithm

References

  1. S. Y. Barykin, L. N. Borisoglebskaya, V. V. Provotorov, I. V. Kapustina et al. Sustainability of management decisions in a digital logistics network//Sustainability (Switzerland). 2021. 13 (16). 9289.
  2. S. L. Podvalny, V. V. Provotorov, E. S. Podvalny. The controllability of parabolic systems with delay and distributed parameters on the graph//Procedia Computer Sciense. 2017. Vol. 103. P. 324-330.
  3. V. V. Provotorov, E. N. Provotorova. Optimal control of the linearized Navier-Stokes system in a netlike domain//Vestnik of Saint Peterburg University. Applied Mathematics. Computer Science. Control Processes, 2017. Vol. 13. Iss. 4. P. 431-443. https://doi.org/10.21638/11701/spbu10.2017.409.
  4. M. A. Artemov, E. S. Baranovskii, A. P. Zhabko, V. V. Provotorov. On a 3D model of non-isothermal flows in a pipeline network//Journal of Physics. Conference Series. 2019. Vol. 1203. Article ID 012094. https://doi.org/10.1088/1742-6596/1203/1/012094.
  5. V. V. Provotorov, S. M. Sergeev, V. N. Hoang. Point control of differential-difference system with distributed parameters on the graph//Vestnik of Saint Petersburg University. Applied Mathematics. Computer Science. Control processes. 2021. Vol. 17. Iss. 3. P. 277-286.
  6. E. S. Baranovskii, V. V. Provotorov, M. A. Artemov, A. P. Zhabko. Non-isothermal creeping flows in a pipeline network: existence results//Symmetry. 2021. V. 13.
  7. M. Matsuda, T. Nishi, M. Hasegawa, S. Matsumoto. Virtualization of a supply chain from the manufacturing enterprise view using e-catalogues//Procedia CIRP. 2019. 81. 932-937. https://doi.org/10.1016/j.procir.2019.03.230.
  8. S. Mitra. Inventory management in a two-echelon closed-loop supply chain with correlated demands and returns//Comput. Ind. Eng. 2012. 62. 870-879. https://doi.org/10.1016/j.cie.2011.12.008.
  9. S. Pan. Opportunities of product-service system in physical internet//Procedia CIRP. 2019. 83. 473-478. https://doi.org/10.1016/j.procir.2019.03.107.
  10. S. M. Sergeev, T. I. Sidnenko, D. B. Sidnenko. Distribution centers for agriculture, their modeling//In: International Scientific School «Paradigma» Summer-2016 Selected Papers. Yelm, WA, USA, 2016. P. 92-97.
  11. L. N. Borisoglebskaya, I. A. Mironova, S. M. Sergeev. Modeling of commercial activity of enterprises in terms of innovative proposals//Innovations. 2013. № 1 (171).
    P. 107-111.
  12. H. Aslam, A. Q. Khan, K. Rashid, S. Rehman. Achieving supply chain resilience: the role of supply chain ambidexterity and supply chain agility//J. Manuf. Technol. Manag. 2020. 31. 1185-1204. https://doi.org/10.1108/JMTM-07-2019-0263.
  13. S. Bag, L. C. Wood, S. K. Mangla, S. Luthra. Procurement 4.0 and its implications on business process performance in a circular economy//Resour. Conserv. Recycl. 2020. 152. 104502. https://doi.org/10.1016/j.resconrec.2019.104502.
  14. G. Frederico, J. A. Garza-reyes. 2020. Supply chain strategy reboot — Supply Chain Management Review.
  15. B. Sarkar, R. Guchhait, M. Sarkar et al. Impact of safety factors and setup time reduction in a two-echelon supply chain management//Robot. Comput. Integr. Manuf. 2019. 55. 250-258. https://doi.org/10.1016/j.rcim.2018.05.001.
  16. V. Scherbakov, G. Silkina, Logistics of smart supply chains//Proc. Int. Conf. Digit. Technol. Logist. Infrastruct. (ICDTLI 2019). St. Petersburg, Russ., 4-5 April, 2019. 66-71. https://doi.org/10.2991/icdtli-19.2019.15.
  17. Y. Zhang, G. H. Huang, L. He. A multi-echelon supply chain model for municipal solid waste management system//Waste Manag. 2014. 34. 553-561.https://doi.org/10.1016/j.wasman.2013.10.002.
  18. S. M. Sergeev. Expansion of DEA methodology on the multimodal conception for the 3PL//In: Modern informatization problems in simulation and social technologies Proceedings of the XXIII-th International Open Science Conference. Editor in Chief O.Ja. Kravets. 2018. P. 169-176.
  19. V. Scherbakov, G. Silkina. Conceptual model of Logistics Vocational Education in the digital economy//Proc. Int. Conf. Digit. Technol. Logist. Infrastruct. (ICDTLI 2019). St. Petersburg, Russ., 4-5 April, 2019. 120-125. https://doi.org/10.2991/icdtli-19.2019.24.

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