The article addresses the urgent problem of managing distributed warehouse-type organizational systems under conditions of extreme environmental entropy typical for modern e-commerce. It is shown that traditional discrete-event and agent-based modeling methods face the computational "curse of dimensionality" and delayed reactivity, precluding their direct application for real-time logistics network control. Based on the integration of systems analysis and the theory of active systems, mathematical formalization and decomposition of the aggregate uncertainty vector into three basic components is proposed: external stochastic, internal technological, and behavioral (subjective). The main result of the study is the development of structural and functional architecture for a hybrid intelligent control system based on a dynamic digital twin of the organization. The operation of three interconnected loops (predictive-analytical, dynamic dispatching, and adaptive-motivational) is described, where heavy step-by-step simulations are replaced by high-speed neural network surrogate models. It is substantiated that the proposed approach provides sub-millisecond rebuilding of conflict-free picking trajectories and enables continuous indirect identification of latent personnel states (fatigue and motivation levels), effectively minimizing information asymmetry and opportunistic agent behavior.
1. Novikov D.A. Theory of Management of Organizational Systems. Moscow: LENAND; 2022. 500 p. (In Russ.).
2. Novikov D.A. Management Methodology. Moscow: Librokom; 2011. 128 p. (In Russ.).
3. Boysen N., de Koster R., Weidinger F. Warehousing in the e-commerce era: A survey. European Journal of Operational Research. 2019;277(2):396–411. https://doi.org/10.1016/j.ejor.2018.08.023
4. Gu J., Goetschalckx M., McGinnis L.F. Research on warehouse operation: A comprehensive review. European Journal of Operational Research. 2007;177(1):1–21. https://doi.org/10.1016/j.ejor.2006.02.025
5. Zhen L., Li H. A literature review of smart warehouse operations management. Frontiers of Engineering Management. 2022;9(10):31–55. https://doi.org/10.1007/s42524-021-0178-9
6. Ivanov D. Digital supply chain management and technology to enhance resilience by building and using end-to-end visibility during the COVID-19 pandemic. IEEE Transactions on Engineering Management. 2021;71:10485–10495. https://doi.org/10.1109/TEM.2021.3095193
7. Ivanov D., Dolgui A. A digital supply chain twin for managing the disruption risks and resilience in the era of Industry 4.0. Production Planning & Control. 2020;32(9):775–788. https://doi.org/10.1080/09537287.2020.1768450
8. Gerlach B., Zarnitz S., Nitsche B., Straube F. Digital Supply Chain Twins – Conceptual Clarification, Use Cases and Benefits. Logistics. 2021;5(4):86. https://doi.org/10.3390/logistics5040086
9. Van der Aalst W. Process Mining: Overview and Opportunities. ACM Transactions on Management Information Systems. 2012;3(2):7. https://doi.org/10.1145/2229156.2229157
10. Kaiblinger A., Woschank M. State of the Art and Future Directions of Digital Twins for Production Logistics: A Systematic Literature Review. Applied Sciences. 2022;12(2):669. https://doi.org/10.3390/app12020669
11. Wurm B., Becker M., Pentland B., et al. Digital Twins of Organizations: A Socio-Technical View on Challenges and Opportunities for Future Research. Communications of the Association for Information Systems. 2023;52:552–565. https://doi.org/10.17705/1CAIS.05223
12. Maheshwari P., Kamble S., Kumar S., Belhadi A., Gupta Sh. Digital twin-based warehouse management system: a theoretical toolbox for future research and applications. The International Journal of Logistics Management. 2023;35(4):1073–1106. https://doi.org/10.1108/IJLM-01-2023-0030
13. Elbouzidi A.D., El Cadi A.A., Pellerin R., Lamouri S., Valencia E.T., Bélanger M.-J. The Role of AI in Warehouse Digital Twins: Literature Review. Applied Sciences. 2023;13(11):6746. https://doi.org/10.3390/app13116746
14. Bélanger M.-J., Pellerin R., Lamouri S. A Literature Review on Digital Twins in Warehouses. Procedia Computer Science. 2023;219(7-8):370–377. https://doi.org/10.1016/j.procs.2023.01.302
15. Aretoulaki E., Ponis S.T., Plakas G., Tzanetou D. Discrete Event Simulation and Digital Twins in Warehouse Logistics: A Bibliometric and Content Analysis-Based Systematic Literature Review. International Journal of Computer Integrated Manufacturing. 2024;37(10-11):1376–1403. https://doi.org/10.1080/0951192X.2024.2314772
16. Le Th.V., Fan R. Digital Twins for Logistics and Supply Chain Systems: Literature Review, Conceptual Framework, Research Potential, and Practical Challenges. Computers & Industrial Engineering. 2023;187(3):109768. https://doi.org/10.1016/j.cie.2023.109768
Dorofeev Artem Evgenievich
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Peter the Great St. Petersburg Polytechnic University
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