04640nam a22006015i 4500 978-3-031-50036-7 DE-He213 20251030111732.0 cr nn 008mamaa 240320s2024 sz | s |||| 0|eng d 9783031500367 978-3-031-50036-7 10.1007/978-3-031-50036-7 doi TK5101-5105.9 TJK bicssc TEC041000 bisacsh TJK thema Advances in Computational Logistics and Supply Chain Analytics [electronic resource] / edited by Ibraheem Alharbi, Chiheb-Eddine Ben Ncir, Bader Alyoubi, Hajer Ben-Romdhane. 1st ed. 2024. Cham : Springer Nature Switzerland : Imprint: Springer, 2024. XIV, 196 p. 40 illus., 30 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Unsupervised and Semi-Supervised Learning, 2522-8498 Introduction -- Innovative logistic techniques and Tools in Industry 4.0 -- Predictive analytics for quality control of logistic processes -- Artificial intelligence systems for smart logistics in the medicine sector -- Supply-Chain Management: Automating the purchase process based on machine learning techniques -- Multi Criteria Decision Making applications in Supply Chain Management -- Consumers’ Acceptance of Drones for last-mile delivery in emerging economy -- Evaluation methods to mitigate the risks of price fluctuations on inventory in contemporary economies -- Overview of using augmented reality techniques in logistics -- Computational methods for scheduling problems -- Digitalization and automation of supply chain processes -- Reverse Logistics: Evaluation of practices in hospitals in Saudi Arabia -- Combining Global Optimization Algorithms with Live Google Maps for Solving the Vehicle Routing Problem -- Conclusion. . This book provides advances in computational logistics and supply chain analytics. The authors include innovative data-driven and learning-based approaches, methods, algorithms, techniques, and tools that have been designed or applied to create and implement a successful logistics and supply chain management process. This book highlights the state of the art and challenges related to the design and the application of computational methods to solve logistic and supply chain management problems. The authors present recent computational logistic methods and supply chain analytics techniques designed and applied to support managers in improving such complex processes. This book broadly covers recent computational methods and techniques applied to ensure continuous improvement of transport, logistic, and supply chain management processes. Readers can rapidly explore these new methods and their applications to solve such complex problems. Highlights the importance of embedding and using computational methods to improve supply chain processes; Presents machine learning and data analytics techniques to solve supply chain optimization problems; Gives readers design and applications of computational methods automate transport, logistic and supply chain processes. . Telecommunication. Business logistics. 61225 Facility management. Industrial Management. 58197 Communications Engineering, Networks. Supply Chain Management. 66371 Facility Management. Industrial Management. 58197 Alharbi, Ibraheem. editor. edt http://id.loc.gov/vocabulary/relators/edt 73487 Ben Ncir, Chiheb-Eddine. editor. edt http://id.loc.gov/vocabulary/relators/edt 73488 Alyoubi, Bader. editor. edt http://id.loc.gov/vocabulary/relators/edt 73489 Ben-Romdhane, Hajer. editor. edt http://id.loc.gov/vocabulary/relators/edt 73490 SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031500350 Printed edition: 9783031500374 Printed edition: 9783031500381 Unsupervised and Semi-Supervised Learning, 2522-8498 68420 https://doi.org/10.1007/978-3-031-50036-7 ZDB-2-ENG ZDB-2-SXE 58491 58491