Advances in Computational Logistics and Supply Chain Analytics (Unsupervised and Semi-Supervised Learning)
by: Ibraheem Alharbi (Editor),Chiheb-Eddine Ben Ncir(Editor),Bader Alyoubi(Editor),Hajer Ben-Romdhane(Editor)&1more
Publisher: Springer
Edition: 2024th
Publication Date: 21 Mar. 2024
Language: English
Print Length: 210 pages
ISBN-10: 3031500350
ISBN-13: 9783031500350
Book Description
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.
About the Author
From the Back Cover 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.
About the Author Ibraheem Alharbi is currently the dean of the College of Business at the University of Jeddah. He serves as Associate Professor in the MIS Department, College of Business, University of Jeddah. His research interests include business and information ethics, information privacy and electronic commerce.Chiheb-Eddine Ben Ncir is currently Associate Professor at the University of Jeddah and a member of LARODEC laboratory, University of Tunis. His research interests concern machine learning methods with a special emphasis on Big data clustering. Bader Alyoubi is currently the dean of the College of Sports Sciences at the University of Jeddah and serves as Professor of Management Information Systems at the same university. His research focuses on decision support systems and knowledge management techniques. Hajer Ben-Romdhane is an Assistant Professor in the Department of Computer Science at Institut Supérieur de Gestion,University of Tunis, Tunisia, and a member of LARODC laboratory. Her research interests include modeling of complex problems and the design of decision support systems.
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