Open Access
Issue |
E3S Web Conf.
Volume 621, 2025
Second International Conference on Green Energy, Environmental Engineering and Sustainable Technologies 2024 (ICGEST 2024)
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|
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Article Number | 03013 | |
Number of page(s) | 9 | |
Section | Sustainable Technology for Environmental Protection | |
DOI | https://doi.org/10.1051/e3sconf/202562103013 | |
Published online | 19 March 2025 |
- A. Orozonova, S. Gapurbaeva, A. Kydykov, O. Prokopenko, G. Prause, S. Lytvynenko, Application of smart logistics technologies in the organization of multimodal cargo delivery. Transportation Research Procedia 63, 1192-1198 (2022). [CrossRef] [Google Scholar]
- W. Bo, M. Grygorak, V. Voitsehovskiy, S. Lytvynenko, T. Gabrielova, L. Lytvynenko, Y. Ivanov, Assessment of the implementation of a cargo traffic management system. Comptes rendus de l’Acade’mie bulgare des Sciences 4(72), 503–509 (2019). [Google Scholar]
- O. Ozerova, S. Lytvynenko, R. Sushchenko, Y. Zapara, P. Ovchar, Y. Lavrushchenko, Factors influencing the modelling of transport flow dynamics in cities. Comptes Rendus de L’Academie Bulgare des Sciences 75(2), 259–265 (2022). [Google Scholar]
- S. Lytvynenko, O. Petrenko, T. Luchnikova, O. Vysochylo, M. Kutsenko, Transformation of Strategic Management Principles of Air Transport and Logistics Enterprises in Conditions of Instability. Communications – Scientific Letters of the University of Žilina 25(3), A111–A123 (2023). [Google Scholar]
- W. Bo, M. Grygorak, V. Voitsehovskiy, S. Lytvynenko, T. Gabrielova, L. Lytvynenko, Y. Ivanov, A.Vidovic, Cargo flows management model of network air carrier. Economic Studies journal 4, 118–124 (2019). [Google Scholar]
- Y. Sen, V. Voitsehovskiy, S. Lytvynenko, I. Borets, S. Rusanova, L. Lytvynenko, Realization of a nonlinear multiproduct model of cargo traffic management of the network air carrier. Comptes Rendus de l’Acade’mie Bulgare des Sciences 74(4), 561–567 (2021). [Google Scholar]
- M. H. Alkinani, A. Ali Almazroi, M. Adhikari, V. G. Menon, Design and analysis of logistic agent-based swarm-neural network for intelligent transportation system. Alexandria Engineering Journal 61(10), 8325–8334 (2022). [CrossRef] [Google Scholar]
- A. Mohandu, M. Kubendiran, Survey on Big Data Techniques in Intelligent Transportation System (ITS). Materials Today: Proceedings 47 (Part 1), 8–17 (2021). [Google Scholar]
- T. Kavitha, N. Pandeeswari, R. Shobana, V.R. Vinothini, K. Sakthisudhan, A. Jeyam, A. Jasmine Gnana Malar, Data congestion control framework in Wireless Sensor Network in IoT enabled intelligent transportation system. Measurement: Sensors 24, 100563 (2022). [Google Scholar]
- C. Bolaños, B.Rojas, R. Salazar-Cabrera, G. Ramírez-González, Á. Pachón de la Cruz, J. M. Madrid Molina, Fleet management and control system for developing countries implemented with Intelligent Transportation Systems (ITS) services. Transportation Research Interdisciplinary Perspectives 16, 100694 (2022). [Google Scholar]
- K. Shaaban, M. Elamin, M. Alsoub, Intelligent Transportation Systems in a Developing Country: Benefits and Challenges of Implementation. Transportation Research Procedia 55, 1373–1380 (2021). [CrossRef] [Google Scholar]
- S. Panchenko, O. Ohar, G. Shelekhan, E. Skrebutene, Optimization of transport system operation using ranking method. Procedia Computer Science 149, 110–117 (2019). [CrossRef] [Google Scholar]
- T. Butko, S. Prodashchuk, G. Bogomazova, G. Shelekhan, M. Prodashchuk, R. Purii, Improvement of technology for management of freight rolling stock on railway transport. Eastern-European Journal of Enterprise Technologies 3 (3/87), 4–11 (2017). [CrossRef] [Google Scholar]
- R. Sushchenko, Y. Zapara, V. Saienko, V. Kostiushko, L. Lytvynenko, S. Pron, Urban transport, logistics, and tourism: Review of a cutting-edge socially-oriented approach to industrial development. Acta Scientiarum Polonorum, Administratio Locorum 22(1), 101–111 (2023). [CrossRef] [Google Scholar]
- О. Lavrukhin, V. Zapara, Y. Zapara, O. Shapatina, G. Bogomazova, Investigation into the bimodal transportation process by modelling rail module states. Transport Problems 12(2), 99–112 (2017). [CrossRef] [Google Scholar]
- V. Pysmak, L. Mazhnyk, Improvement of efficiency of enterprises operating in the services sector on the basis of logistics concepts. Economic Annals-ХХI 1-2, 101–104 (2016). [CrossRef] [Google Scholar]
- Z. Drinke, L. Mazhnyk, R. Zvirgzdina, T. Mokiienko, L. Holovash, H. Kryshtal, Digital economy: opportunities for transformation of entepreneurial structures. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu 1, 140–146 (2024). [Google Scholar]
- K. Marintseva, G. Yun, I. Vasilenko, Delivery of special cargoes using the unmanned aerial vehicles. Research Anthology on Reliability and Safety in Aviation Systems, Spacecraft, and Air Transport. IGI Global, 1564–1587 (2021). [Google Scholar]
- L. Savchenko, N. Biletska, O. Buriachenko, M. Shmahelska, І. Коpchykova, I. Vasylenko, Economic and Information Principles for Cargo Delivery Management in Global Network Supply Chains. International Journal of Computer Science and Network Security 21(12), 443-450 (2021). [Google Scholar]
- A. Renda, S. Schwaag Serger, D. Tataj, A. Morlet et al., Industry 5.0, a transformative vision for Europe – Governing systemic transformations towards a sustainable industry, Publications Office of the European Union (2021). [Google Scholar]
- R. Gizetdinov, Automation and digitalisation of transport forwarding services or logistics. Infrastructure Asset Management 11(2), 100–107 (2024). [CrossRef] [Google Scholar]
- K. Nowacki, A.Wierzbic, Utilizing artificial intelligence in transport demand planning for a company providing logistics services in the trade industry. Procedia Computer Science 246, 5575–5584 (2024). [Google Scholar]
- S. Abbasi, Ç. Sıcakyüz, E. Gonzalez, P. Ghasemi, A systematic literature review of logistics services outsourcing. Heliyon 10(13), e33374 (2024). [Google Scholar]
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