Hao Yu received his Ph.D. degree in Applied Mathematics and Computational Engineering from UiT—The Arctic University of Norway in 2018. At the moment, he is a tenured Associate Professor and the Director of Master Program of Industrial Engineering at UiT—The Arctic University of Norway. His research focuses on applied operations research and real-problem-driven model development to solve complex problems in sustainable supply chain, reverse logistics, location and network design, service systems, scheduling, and smart manufacturing and logistics in Industry 4.0/5.0. He is the Associate Editor of IEEE Transactions on Intelligent Transportation Systems and World Journal of Engineering, and editorial member of several other journals. He also manages or being a key member of several national and international projects, and his current research focuses on the combination of predictive analytics, prescriptive analytics, and descriptive analytics in an Industry 5.0 enabled Smart Digital Logistics Twin that can be used in, for example, reverse logistics, humanitarian/epidemic logistics, and reconfigurable remanufacturing systems.

• Preface. Distribution and Logistics Network Design in Industry 5.0: Models, Methods, and the Impact of Generative AI and Large Language Models. Distribution and Logistics Network Design Using Digital Twin: Concepts, Methods, and Applications. Artificial Intelligence and Data-driven Smart Transportation and Logistics: Unsupervised Learning Models and Ensemble Learning Models. Artificial Neural Network Methods in Smart Logistics: Concept, Methods, and Applications. Embedding Social Value in Sustainable Transport and Smart Logistics Systems. Extended Reality in Warehousing: Bridging Industry 4.0 and 5.0 for Smart Logistics. Circular Economy Principles and Sustainable Logistics Practices in Industry 5.0. Reverse Logistics in Industry 5.0: Opportunities and Challenges: A Systematic Literature Review and Research Agenda.

Hao Yu received his Ph.D. degree in Applied Mathematics and Computational Engineering from UiT—The Arctic University of Norway in 2018. At the moment, he is a tenured Associate Professor and the Director of Master Program of Industrial Engineering at UiT—The Arctic University of Norway. His research focuses on applied operations research and real-problem-driven model development to solve complex problems in sustainable supply chain, reverse logistics, location and network design, service systems, scheduling, and smart manufacturing and logistics in Industry 4.0/5.0. He is the Associate Editor of IEEE Transactions on Intelligent Transportation Systems and World Journal of Engineering, and editorial member of several other journals. He also manages or being a key member of several national and international projects, and his current research focuses on the combination of predictive analytics, prescriptive analytics, and descriptive analytics in an Industry 5.0 enabled Smart Digital Logistics Twin that can be used in, for example, reverse logistics, humanitarian/epidemic logistics, and reconfigurable remanufacturing systems.

• Preface. Distribution and Logistics Network Design in Industry 5.0: Models, Methods, and the Impact of Generative AI and Large Language Models. Distribution and Logistics Network Design Using Digital Twin: Concepts, Methods, and Applications. Artificial Intelligence and Data-driven Smart Transportation and Logistics: Unsupervised Learning Models and Ensemble Learning Models. Artificial Neural Network Methods in Smart Logistics: Concept, Methods, and Applications. Embedding Social Value in Sustainable Transport and Smart Logistics Systems. Extended Reality in Warehousing: Bridging Industry 4.0 and 5.0 for Smart Logistics. Circular Economy Principles and Sustainable Logistics Practices in Industry 5.0. Reverse Logistics in Industry 5.0: Opportunities and Challenges: A Systematic Literature Review and Research Agenda.