Artificial Intelligent Techniques for Wireless Communication and Networking. Группа авторов

in detail with its supply chain partners. As any other approach to digital technology, training is another factor that takes considerable time and money commitment. Business efficiency will be impacted because supply chain suppliers will need to work with AI supplier to create a training solution which is cost-effective and effective during the integration procedure.

3.4 Conclusion

More and more sectors and realms of our lives are being conquered by artificial intelligence and machine learning, and logistics is no exception. In the supply chain sector, AI and logistics machine learning can be an excellent aid. Using them, systems can be streamlined, errors that humans can create or miss can be avoided, potential possibilities and problems can be anticipated. In terms of global supply chain and logistics, Artificial Intelligence is becoming highly explosive. Many logistics officials agree that a significant transition is likely to occur in these regions. It can interrupt the ongoing development of advanced and digital technologies such as machine learning, artificial intelligence, processing of natural languages (NLP), etc. and encourage progress in these sectors. Therefore, this study provides a complete theory behind logistics and supply chain in terms of impacts and trends and describes briefly about how logistics and supply chain can propel the business into the future—harnessing automation.

References

      1. https://www.europeanbusinessreview.com/artificial-intelligence-ai-in-supply-chain-planning-the-future-is-here-now/

      2. https://supplychainbeyond.com/6-ways-ai-is-impacting-the-supply-chain/

      3. https://www.tristatetechnology.com/blog/how-ai-can-transform-the-logistics-and-supply-chain-management-industry/

      4. Abdullayeva, A., Impact of artificial intelligence on agricultural, healthcare and logistics industries. Ann. Spiru Haret Univ. Econom. Ser., 19, 167–175, 2019.

      5. Baryannis, G., Validi, S., Dani, S., Antoniou, G., Supply Chain Risk Management and Artificial Intelligence: State of the Art and Future Research Directions. Int. J. Prod. Res., 57, 2179–2202, 2018.

      6. Devi, N. and Paul, V.M.T., Artificial Intelligence: Pertinence in Supply Chain and Logistics Management. Xi’an Jianzhu Keji Daxue Xuebao/J. Xi’an Univ. Archit. Technol., 12, 701–709, 2020.

      7. Gunasekaran, A. and Ngai, E., Expert systems and artificial intelligence in the 21st century logistics and supply chain management. Expert Syst. Appl., 41, 1–4, 2014.

      8. Hellingrath, B. and Lechtenberg, S., Applications of Artificial Intelligence in Supply Chain Management and Logistics: Focusing Onto Recognition for Supply Chain Execution: Bridging the Gap Between Information Systems Research and Practice, Springer, 2019. https://citations.springernature.com/item?doi=10.1007/978-3-030-06234-7_27

      9. Kar, U., Dash, R., McMurtrey, M., Rebman, C., Application of Artificial Intelligence in Automation of Supply Chain Management. J. Strategic Innov. Sustainability, 14, 43–53, 2019.

      10. Kowalski, M., Zelewski, Bergenrodt, D., Klüpfel, H., Application of New Techniques of Artificial Intelligence in Logistics, pp. 323–328, European simulation and modelling conference, 2012.

11. Klumpp, M., Automation and artificial intelligence in business logistics systems: Human reactions and collaboration requirements. Int. J. Logist., 21, 224–242, 2017, https://doi.org/10.1080/13675567.2017.1384451

      12. Klumpp, M., Artificial Intelligence Applications, Springer, 2019.

      13. Makkar, S., Naga Rama Devi, G., Solanki, V., Applications of Machine Learning Techniques in Supply Chain Optimization, in: ICICCT 2019 – System Reliability, Quality Control, Safety, Maintenance and Management, pp. 861–869, Springer, 2020.

      14. Min, H., Artificial intelligence in supply chain management: Theory and applications. Int. J. Logist.-Res. Appl., 13, 13–39, 2010.

      15. Ruamsook, K. and Tracey, S., Jr, C., Supply Chain Management in the Age of AI Revolution, 2019.

      16. Shanmugam, B., Palaniswami, V.-R., Venkatesh, R.S., Strategies for Privacy Preserving Publishing of Functionally Dependent Sensitive Data: A State-ofthe-Art Survey. Aust. J. Basic Appl. Sci., 8, 5, 353–365, 2014.

      17. Thamer, H., Börold, A., Benggolo, A., Freitag, M., Artificial intelligence in warehouse automation for flexible material handling, in: 9th International Scientific Symposium on Logistics in Magdeburg (June 13-14, 2018), pp. 143– 149, BVL, Bremen, 2018.

      18. Thành Long, N., Artificial Intelligent (AI) and the Future of supply chain, Opulence, 2, 1, 1–44, 2018.

      19. Toorajipour, R., Sohrabpour, V., Nazarpour, A., Oghazi, P., Fischl, M., Artificial intelligence in supply chain management: A systematic literature review. J. Bus. Res., 122, 502–517, 2020.

      20. Xing, B., Gao, W.-J., Battle, K., Marwala, T., Nelwamondo, F., Artificial Intelligence in Reverse Supply Chain Management: The State of the Art, 2010. https://arxiv.org/abs/1012.4046

      21. Zhang, Y., The application of artificial intelligence in logistics and express delivery. J. Phys.: Conf. Ser., 1325, 012085, 2019.

      1 * Corresponding author: [email protected]